1. No category

Business Aspects of the
Internet of Things
Seminar of advanced topics, FS 2011,
Florian Michahelles (ed.)
This report reflects on the business opportunities of an
emerging Internet of Things. All articles have been prepared by
students participating in the Seminar of advanced topics in
spring 2011.
http://www.im.ethz.ch/education/FS11/iot_sem
The Internet of Things describes the technical implementation of connecting objects and
devices from real-world processes for establishing multi-purpose services. In order to
establish this distributed collaboration among things various kinds of communication
infrastructures ranging from RFID tags to low-cost IPv6 network devices have to be brought
together. Collecting data from physical things is believed to provide new insights into
business processes, consumer actions and all kinds of human activities which should fertilize
new business models and services.
This report provides an overview of a selection of Internet of Things business ideas
elaborated by 8 students as part of a research seminar held during Spring 2011. Students
introduced their ideas in 15min talks to the class and lead a discussion with the other
students. The results then were summarized in short reports.
These proceedings present a selection of the research papers composed by the students as
part of this course. The following articles provide concise summaries of related work in the
field and aim at collecting useful sources to the Internet of Things for novices, practitioners
and other students interested in this field.
Thank you very much to all students visiting “Business Aspects of the Internet of Things” in
spring 2011 at ETH Zurich, details to be found here:
http://www.im.ethz.ch/education/FS11/iot_sem
Florian Michahelles
Zurich, Switzerland, July 20, 2011
Table of Contents
Business Aspects of the Internet of Things
Seminar of advanced topics, FS 2011, Florian Michahelles
Some aspects about the internet of things, the advantages and challenges
Yannick Erb
3
Impacts of Mobile Technologies on Travel Insurance
Lukas Ackermann
11
Wireless sensor network for disaster prevention of tunnels built by New Austrian
Tunnelling Method
Ruzena Chamrova
16
Concept for a Basic Soccer Analysis Service
Patrick Haas
21
The value of “the Internet of Things-mashup” for enterprises
Dominique Mirandolle
27
Smart Cities and Internet of Things
Oliver Haubensak
33
Hability - An integrated smart meter framework for home and mobility use
Daniel Mauch
40
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Some aspects about the internet of things, the advantages and challenges
Yannick Erb
Management, Technology and Economics
ETH Zürich
[email protected]
consumption computers on the other side, here the
difference clearly lies in the size of the products.
In today’s world, we register about five billion
devices (mobile phones, personal computers, MP3
players, cameras…) and a population of 6.7 billion
people where only 1.5 billion are using the internet.
Even if those numbers seem huge, compared to all
things that are yearly produced (about 100 billion), it is
only a tiny part of it. Now imagine that in the future
those products might be equipped with minicomputers.
Based on the above-mentioned facts, it seems clear that
the people won’t be able and willing to communicate
with all those smart things, that’s why a new network
infrastructure might be required, such as the internet of
things.
The internet is being used today not only for
communication reasons, more and more also for video
streaming and other big file downloads. That’s why the
last mile in the internet has been increased during the
last years extremely. A household nowadays connects
to the internet with a bandwidth of at least 1 Mbit/s.
With new technologies such as fiber optics, the
bandwidth will increase soon up to 50 – 100 Mbit/s.
These are huge velocity dimensions compared to a
RFID tag, where the transmission speed is only about
100 kBit/s.
Assuming that in the future a lot of things will be
tagged with a minicomputer or sensor, addressing
schemes needs to be improved, because the actual
protocol of addressing used for the internet requires too
much capacity for those small devices. That’s why
alternative technologies and standards such as IPv6
(new internet protocol), EPC, ucode and so on are
generated. To ensure a complete compatibility between
those smart things and the computers, a global standard
protocol would be required. Another big difference
between the IoT and the internet considers the service
range they offer. While the internet-based services are
targeted towards human beings as users, such as the
World Wide Web, email, file sharing, chat, and rating,
the attributed of the internet of things almost
completely exclude humans from direct intervention.
Those statements showed quickly the main differences
between the internet and the internet of things.
Abstract
The internet of things (IoT) expands the internet
through smart things. Nowadays, computers and
mobile phones connect only via manual input from
humans to the internet. The overall goal is to create
through sensors and sensor networks a communication
platform that allows independent interactions between
those smart products, because in the future a huge
amount of minicomputers and sensors are expected.
Through the integration of new technologies, the gap
between the real world and the digital world decreases
which leads to a higher accuracy because of avoiding
media breaks (see chapter 2.1). Problems occur
regarding the privacy. Through the overall and free
share of information to the whole world, it is nearly
impossible to track and trace everything back and still
have the entire control of information sharing. The
overall gain of the internet of things still outbalances
this risk of losing privacy and control. But in the end,
everyone takes his own decision being part or not of
the entire system.
1. Introduction
The internet of things expands the internet by smart
products. Smart products differ from usual items
through their ability to communicate among each other.
Looking at today’s internet, the typical procedure of
using it happens through the manual input through a
human. So taking all the mobile devices and
computers, they are kind of isolated to the real world,
because their interactions depend on a manual input
from outside.
Let’s compare the most important differences
between the internet and the internet of things.
Beginning with the hardware, the criteria for both
technologies are very different [2]. Having the internet
with high capacity computers on the nerve ends which
require direct access to the power grid on the one side,
and very small or almost invisible low-end and low
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
each other within local networks and, ultimately,
connected to the wider network of networks – the
Internet.” [17]
Switching now to an IP point of view, here the focus
lies mainly on the smart devices that are connected and
communicate among each other [4]. A further point in
this definition is the diminishing gap between the real
world and the digital world. The technology would
mainly bring both worlds closer together and enable
smart things to interact freely.
A fourth view about the internet of things gives us
Prof. Dr.-Ing. Bernd Scholz-Reiter. He’s the managing
director of the Bremer Institut für Produktion und
Logistik GmbH at the University of Bremen [5]. The
view he shares is the one that interactions between
objects will emerge, but therefore the convergence of
technologies necessary [6]. The definitions from the IP
point of view and this one from Prof. Scholz-Reiter are
quite the same. Both rely on the communication among
smart things and about improved technologies.
Prof. Dr. Elgar Fleisch adds another point to all
previews arguments. Each thing should get its own
minicomputer and a direct connection to the internet to
enable the communication among them [2].
As seen, overall all definitions point out the
communication through the internet between tagged
things. In addition emerging technologies are
indispensable to reach the goals. But still, while
digging deeper in those point of views, differences
become visible as mention above.
The overall goal is to generate automatic
interactions among products which are connected to the
internet. The idea behind the IoT is that every real
world object becomes a part of the internet whereby the
gap between the digital and the real world gets smaller
and smaller (see Fig. 1) [1].
Fig. 1: Diminishing gap through smart things between the
real world and the digital world. (Source [1])
In the last years, the number of minicomputers
increased dramatically and on the opposite, the cost for
those minicomputers decreased. The consequence of
this evolution is that the margin on the products will
decrease. But based on this fact, the question arises,
how to get back the “lost” margin? The key here is to
change the product-based view to a service-oriented
view, hence improve your service related to your
product to improve margin and increase your
competitive advantage.
2.1 Internet of things and what’s next?
2. What is the internet of things?
Let’s now have a look how the internet of things
could improve in the future. Trillions of smart things
communicating with one another will challenge the
technology and its capacity [16]. The digital and the
physic world will fuse by bringing different concepts
and technical components together:
 Pervasive networks
 Miniaturization of devices
 Mobile communication
 New models for business processes
Business benefits such as the high-resolution
management of assets and products same as improved
life-cycle management can be achieved with the help of
IoT. Even collaboration between enterprises will
enhance remarkable.
The following citation was not worthwhile to rewrite
differently, because it shows perfectly what will be how
connected: “The Internet of Things allows people and
things to be connected Anytime, Anyplace, with
Anything and Anyone, ideally using Any path/network
As you may image, there is not “the” definition of
the internet of things. It depends very much from which
perspective you look at it, or more precisely, in what
industry branch you’re involved. The term Internet of
Things was first mentioned in the year 1999, by Kevin
Ashton [12]. Following we compare four IoT
definitions, beginning with two from the industry sector
and ending with two from an academic point of view.
The International Communication Union ITU
focuses mainly on the definition, that through the IoT
those things will disappear through upcoming
technologies [3]. This statement very much insists on
vanishing products. To get that, new and profound
technologies are necessary.
Now we move to one of the god fathers of IoT, Rob
van Kranenburg. He states that “…increasingly large
numbers of our everyday objects and gadgets will have
some kind of simple communication technology
embedded into them, allowing them to be connected to
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Thereby the accuracy amounts to 97%. But this only
step is just one of many others. The equations for
calculating the accuracy or the failure rate of “x”-media
breaks are the following ones:
Accuracy = 0.97x
or
Failure rate = 1 – 0.97x
and Any service. This implies addressing elements such
as Convergence, Content, Collections (Repositories),
Computing, Communication, and Connectivity in the
context where there is seamless interconnection
between people and things and/or between things and
things so the A and C elements are present and
addressed.”[16]
All mistakes people do sum up to an average master
data accuracy of about 70% (≈ 12 media breaks)!
That’s why people and companies try to avoid media
breaks as much as possible. This can be done through
department-wide information systems e.g. the
mentioned accounting business. Because in such a wide
system, all needed information is saved and available in
this system and no more on a sheet of paper. Having all
data now online or at least on a computer, the media
break between the written paper and the transformation
into a computer system vanishes. Further introductions
help in reducing media breaks:
 Company-wide
enterprise
resource
planning systems
 Cross-company information systems (e.g.
supply chain management)
 Every new generation of information
management
Relating to our earlier definitions of the internet of
things, reducing the media breaks claims to reduce the
gap between the real world and the digital world.
Another very important point is the convergence of
new technologies that allow us to introduce companywide systems that interact automatically without any
external input from humans and provide all updated
data to everyone.
Fig. 2: The communication and connection power of the
internet of things. (Source [16])
2.2 Avoid media breaks through the IoT
A media break describes a transformation of
information between two medium [2]. When
information is converted through human from a piece
of paper into a computer, then we notice one media
break. Because people are not made for doing such
simple and boring work all over the time, they are
prone to do mistakes which in the sum are an important
factor. Since more than 60 years, people are trying to
avoid as much media breaks as possible to enhance the
overall accuracy. This error rate of humans amounts to
3% for each media break.
Now having a quick look at a typical example, we’ll
see how big this mistake can become. Imagine a worker
in the accounting department of a company. His job
contains mainly calculations and bookkeeping. The
transformation from one calculation step (numbers are
given on a sheet of paper and the calculation is done by
typing it into a calculator) adds the first media break.
2.3 Required technologies and IPv6
The implementation of services in the internet of
things relies on some key technologies which we’re
going to discuss below [7]. The underlying technology
is often a wireless sensor network, which relies on
sensing, processing and communication technology.
Sensor: The sensor is probably the most important
part for the internet of things. He is used to collect all
measurable information directly from the real world
(e.g. temperature, pressure, speed, humidity, height,
location, gravitation, heat radiation, brightness…).
Those data can then be used to generate services and
applications. The choice of the sensor depends on the
required precision, value range, environmental
conditions etc. Due to a wide amount of different
sensors for specific applications it depends very much
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
which information can be measured by which sensor.
The price of a sensor is even so an important indicator.
Sensor network: Like there are a lot of different
sensors, there are also a lot of different sensor networks
which are application specific. It depends mainly on
those factors which communication protocol will be
needed [8]:
 How big the data rate needs to be
 How big or low the power consumption
amounts to be
 In what medium (air, water) the sensor
network will work
 Cost
 Complexity of the network
Communication network: For the internet of things
communication networks provide the data transmission
channel. The main challenge today is to create and
enhance the current networks to meet the service
requirements of the internet of things (e.g. low data
rate, low mobility).
Internet of things platform: This platform is
connected to several terminals as well as networks and
systems. They provide the capabilities to different
applications. The big challenge now is to create a
unified service platform that is suitable for applications
of all industries to support cross-sector unified
information services.
2.4 Challenges
After having considered those points mentioned
above, the sensor network technology needs to be
chosen among different ones [9]:
 Bluetooth (range 10 – 100m)
 IrDA (range 0.3 – 1m)
 Wi-Fi (range 30 - 100m)
 ZigBee (range 10 – 100m)
 RFID (range 0.5 – 10m)
 Ultra-Wide Band UWB (range 10 – 50m)
 Near Filed Communication NFC (range
0.1m)
 WirelessHart (range up to 3km)
One of the main challenges for the internet of things
and all the technologies are to transform connected
objects into real actors of the internet [11]. Because for
example a temperature sensor doesn’t measure a
temperature, it measures physical changes occurring
with temperature changes and then coverts the value to
an electrical signal. This example is very simple but
this scenario becomes even more complicated, the
more complex a sensor becomes. Another challenge is
to reduce the size and the costs of those minicomputers
to a minimum, so that a lot of people can gain from this
technology. The power of the internet of things only
arouses, the more smart things exist.
What about all the data that are generated and stored
somewhere through using more and more cloud
computing? The challenge here is try to keep the
threshold of giving information away and getting
service therefore somehow traceable. This risk in
privacy losses needs to be evaluated by each person by
themselves, whether the gain outweighs the loss or vice
versa.
Another very important challenge is the
standardization through all industry branches. Avoiding
this, cross-connections cannot, or only hardly, be
managed.
Fig. 3: Some radio options for wireless sensor networks.
(Source [8])
Sensor networks will soon get the new internet protocol
IPv6. Nowadays the recent internet protocol is IPv4
which offers 232 addresses (≈ 4.3 billions) [10]. Nearly
all of them are assigned which would create a
bottleneck in the future, especially for the internet of
things, where smart things will be connected to the
internet. That’s why the new internet protocol IPv6 is
going to be introduced step by step. This one provides
2128 addresses (≈ 340 sextillions). One week ago, on 8th
of June, the World IPv6 Day was launched [18]. More
than 400 websites (Google, Facebook, Yahoo…)
activated the “Dual-Stack-Mode” of IPv4 and IPv6.
2.5 For which branch of the industry is IoT
important?
This subchapter only sums up for which industry
sectors the internet of things became or will become
very important. Some examples will follow later on.
Not every branch of the industry uses the IoT in the
same way, even so the application varies. Below
summed up in headwords the probably most important
industry sectors using the internet of thing [1]:
 Medical industry
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)









3.2 New healthcare system
Chemical industry
Warehouse
Mobile phones and computers
Car industry
Logistic and supply chain
Food industry
Libraries
Promotions
…
The internet of things is also very important in the
medicine. This example shows briefly what could be
possible using this new technology for a new healthcare
system.
Small computers in clothes like T-shirts or sweater
will be integrated. Those measure permanently the
body temperature and the heart rate and synchronize all
data ongoing with an external server [16]. As soon as
something with your body would be wrong, you’d get a
message to your mobile phone with the information
what’s wrong. If something dramatically like a cardiac
arrest occurs, an alarm including your position (with
the help of a GPS signal) would be automatically sent
to the hospital.
Another example are new toilets that control your
sugar level, blood pressure, body fat and weight in your
urine every time before flushing it away [13]. This
system is already available. A further example is an
electric operated toothbrush that is connected to your
“home healthcare system”. It would check the status of
your teeth (plaque, caries) while your cleaning them. If
the toothbrush would find some abnormalities the data
would be transferred to your dentist, your system
makes an appointment for you at your dentist (assumed
your calendar in your mobile phone is synchronized
with the system) and you get a message with the date
and time of the appointment on your mobile phone.
Imagine you need some medicine regular all the
time, e.g. to lower your blood pressure. Now if the
medicine gets empty, you need new ones and therefore
have to visit a drugstore or your doctor. Basically this
is a waste of time. Now the idea here is to implement in
every package of medicines a small chip and a sensor
in your garbage can at home. So now by throwing the
empty box away, the sensor reads the information on
the chip to know what medicine was thrown away and
orders automatically a new one that arrives directly to
your home within 24 hours.
With the help of new technologies and new
emerging markets, the industry sectors using IoT
increases constantly.
3. Four examples
3.1 Retail store
The Galeria Kaufhof is a big German Warehouse
where you can buy almost everything. There is also
cloth sector in it with more than 30’000 pieces of
clothing [1]. In the example, every piece was tagged
with a chip. Sensors were installed in all dressing
rooms to display all the try-ons.
The goal of that experiment was to display at what
opening hours the ratio of the try-ons and the
corresponding sales was under proportional or over
proportional. With that information the management
could reorganize and optimize for example the time for
the breaks of the sales persons. They also tried to figure
out, what effect corresponds when putting clothes only
in the shelves and when dollies wore them. So with this
simple method and the use of sensors and mini chips,
the sales can be increased and optimized.
3.3 Logistic and supply chain
This example already exists in big medical retailers
here in Switzerland. The idea is mostly the same like
the example above with the medicine and the bin. The
boxes that are filled with medicine in the stock are
tagged with a little chip [1]. The workers take out as
much medicine as they need to fulfill an order and then
put the box back into the shelf. Now when the worker
sees that the box is nearly empty, he simply turn the
box by 180° when he puts it back into the shelf. A
sensor at the shelf recognizes it and orders
Fig. 4: On the horizontal axis you see the opening hours and
on the vertical scale the try-on to corresponding sales ratio.
Blue line: try-ons, red line: corresponding sales. Unexpected
information was displayed, such as that the breaks of
employees around 5 p.m. caused a smaller revenue/try out
ratio. (Source [1])
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
1. Simplified manual proximity trigger: This
simplifies the triggering and speeds up a transaction
while the accuracy is increased. Some examples are
self-checkout, stock-taking and access control in
buildings. The business value is an increase in job
satisfaction; it enables consumer-self-service and
reduces labor costs. The self-service and the higher
speed acts positively for the consumer.
2. Automatic proximity trigger: This driver is pretty
much the same as the first one, but the main difference
is that the self-talking ID automatically triggers a
transaction in a certain room. Two examples here are
asset tracking and car keys. The business values it
creates are cost reductions in process failure and labor.
For the customer it’s mainly an increase in
convenience.
3. Automatic sensor trigger: Through the
introduction of a sensor, the ID is expanded by any
data smart thing can collect (e.g. temperature,
acceleration, localization, humidity, noise, vibrations,
brightness, life signals…). A good example here is this
one from the food industry in chapter 3.4, where
perishable goods are supervised. Through the prompt
process control, process efficiency and effectiveness
are increased same as the quality of products and
services.
4. Automatic product security: This point adds the
security component to the driver. Depending on how
encrypted it should be, the price varies very much. In
practice this method is used in the anti-counterfeiting
industry or for complex access control. The business
and customer value is the increase in trust and related
services.
5. Simple direct user feedback: Smart things provide
a direct feedback (audio signal [beep], visual sign
[LED], haptic effects…) to the user which increases the
local process control and the confidence. This can be
used in digital games or again for perishable goods
(green LED = temperature okay, red LED = not okay).
Through that, processes become more accurate and
faster which leads for the customer in an increase in
convenience and entertainment value.
6. Extensive user feedback: This driver extends the
output to rich services for the consumer. A good
example here is a barcode scanner application for a
mobile phone (freely available) where by scanning the
product barcode, the app searches online the lowest
price near your location. This offers new advertisement
opportunities and additional service revenues for the
business side. Deep product information and again an
increase in convenience result for the customer.
7. Mind changing feedback: A combination of the
real world with the virtual world can manipulate
automatically new medicine at their supplier. This
method is very simple and reduces the cost to order at
the same time.
Another example comes from SenseAware in
corporation with FedEx [14]. The idea behind there, is
a simple transportation box that informs you through an
integrated GPS sensor where your item is. Further it
tells you if the box was opened or exposed to light and
through an integrated temperature sensor it also traces
the temperature.
3.4 Food industry
The last example comes from the food industry
(implementation exists already) [1,15]. Food (here
strawberries) reacts very different on small temperature
changes, some are more perishable than other. Here the
idea is to install temperature sensors in the packages of
perishable food. Those measure permanently the actual
temperature and as soon as the temperature crosses a
certain threshold, an alarm is sent to the warehouse (or
wherever the food is stored at the moment) to inform
their workers to immediately correct the temperature.
This method reduces waste material on the whole
supply chain by almost 50% and increases the profit
and quality each by totally 8%!
Fig. 5: Changes on different factors through the
implementation of temperature sensors among the whole
supply chain. (Source [1])
4. Value drivers
In this chapter the focus will be on the value
applications create to businesses and customers using
the internet of things [2]. Every application relates to at
least one or more of the seven main value drivers listed
below. The first four drivers are based on machine-tomachine communication while the last three are based
on the integration of users.
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
people’s behavior through the introduction of new
technologies. Imagine an application that shows you
how much water you used compared to your wife or
husband or how much pollution you generated by doing
something. The introduction of this driver enables new
emotional product features and services. This can help
to align business goals with green goals. For the
customer, the benefit lies in the ability to improve life
and act responsible in many different ways.
5. Conclusions
The internet of things is undoubtedly going to gain
more and more importance in the near future. The
difference between the internet and the internet of
things is that things become smart through
technological components. Up till now, every action
relies on a manual input through humans. The goal is to
create cheap communication systems that enable the
automatic interaction among those smart products.
Through that, the gap between the real world and the
digital world gets smaller and media breaks can be
avoided. By providing information through the
customers and sharing them for example one some
social platforms, it’s feasible to create service
applications. The success often depends on how many
customers are using the service, the more the better.
The generation of information depends mainly on
what sensor and sensor network is used. Because all of
them are different costly, it is therefore highly
recommended to only build in those sensors and
corresponding networks with features that also are
really used.
As we’ve seen, in almost every branch of the
industry the internet of things is represented. In many
of them, the IoT is even nowadays irreplaceable. With
decreasing costs of the required technologies more
applications are possible. Through the introduction of
game-like applications (compare chapter 4, mind
changing feedback) it is even possible, to change
consumers behavior in a hopefully good direction.
10. References
[1]
E.
Fleisch,
Internet
of
Things,
http://www.im.ethz.ch/education/HS10/MIS_2010
_VL06.pdf
[2]
E. Fleisch, What is the Internet of Things?,
http://www.autoidlabs.org/uploads/media/AUTOID
LABS-WP-BIZAPP-53.pdf
9
[3]
Marc D. Weiser, ITU-T: Global Standards for the
Internet of Things, http://www.itu.int/en/ITUT/techwatch/Pages/internetofthings.aspx
[4]
S. Karnouskos et al., The Internet of Things and
the
Convergence
of
Networks,
http://www.rtcmagazine.com/articles/view/101879
[5]
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Scholz-Reiter,
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2&staff=bsr
[6]
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[7]
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the
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[8]
R. Chamrova, Wireless sensor networks in
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[9]
http://de.wikipedia.org/wiki/Bluetooth
http://de.wikipedia.org/wiki/Irda
http://de.wikipedia.org/wiki/Wlan
http://de.wikipedia.org/wiki/Zigbee
http://de.wikipedia.org/wiki/RFID
http://de.wikipedia.org/wiki/Near_Field_Communi
cation
http://de.wikipedia.org/wiki/UWB
http://de.wikipedia.org/wiki/WirelessHART#Wirel
essHART
[10]
S. Hollenstein et al., Migration to IPv6,
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[11]
H. Sundmaeker et al., Vision and Challenges for
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the
Internet
of
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[12]
http://de.wikipedia.org/wiki/Internet_der_Dinge
[13]
http://articles.cnn.com/2005-0628/tech/spark.toilet_1_toilet-totobathroom?_s=PM:TECH
[14]
http://www.senseaware.com
[15]
http://www.rfidjournal.com/article/view/5191
[16]
http://sintef.biz/upload/IKT/9022/CERPIoT%20SRA_IoT_v11_pdf.pdf
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
[17]
[18]
http://eprints.mdx.ac.uk/2990/1/jisc_rfid.pdf
10
http://www.computerbase.de/news/allgemein/
computerbase/2011/juni/world-ipv6-day-am-8.juni-mit-computerbase/
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Impacts of Mobile Technologies on Travel Insurance
Lukas Ackermann
ETH Zurich, Swiss Federal Institute of Technology
[email protected]
to familiar people and sources of information.
Nevertheless the basic concerns about risks of
travelling are unchanged [1] / [2].
The internet channel has become the favorite
channel for people of all ages to book holidays [2]. As
a consequence also travel insurances are taken out on
the same channel. The recent success of smartphones
has changed the way people access information and
services in the internet. This paper takes a closer look
at the consequences of new technology applications
and the changed customer behavior on the travel
insurance business.
Abstract
Travel insurance is a commoditized insurance
coverage usually sold through third party channels
such as travel agents or online travel portals. New
communication technologies do have a significant
impact on sales processes, after sales services and
claims handling. Case studies illustrate how
technologies are applied and how they change the
interface between insurer and customer. Based on new
technologies innovative business models may be
introduced in order to change today’s travel insurance
market.
2. The Role of Technologies
As in other industries information management and
communication technologies are nowadays of crucial
importance and have a great influence on business
practice [3]. Fleisch [4] refers to the visionary concept
Internet of Things (IOT) as a world of smart things
connected to the internet. Tags and sensors are acting
as nerve endings expanding the internet into virtually
every object and turning it into an accurate copy of the
real world. In the Internet of Things context the
smartphone with its functionalities acts as an extended
sensor for measuring human behavior as well as it
offers access to information.
This huge collection of data will be the basis for a
variety of applications. Loukides [5] points out that
these databases and their combination will lead to new
services: “It's not just an application with data; it's a
data product. Data science enables the creation of data
products.”
1. Introduction
Travelling for business or leisure reasons is a
popular activity not only today but also in history. The
economic prosperity of businesses and households, the
globalization of commerce and the sinking costs for
transportation lead to an ever increasing number of
voyages.
Leaving the familiar surroundings is linked to
emotions of uncertainty and insecurity, but also to
objective exposure of risks.
The travel insurance industry has actually been
around for quite some time. In 1864 the world’s first
travel insurance agency started its business activities
[1]. The Traveler’s Insurance Company was found “for
the purpose of insuring travelers against loss of life or
personal injury while journeying by railway or
steamboat”.
Since that time the face of the travel insurance
industry has changed dramatically and there are all
kinds of risks against which you can take out
insurance. Nowadays clients see accidents, riots and
terrorist attacks as well as illnesses as the most
important risks while travelling as the survey of
Mondial reveals [2]. Travelling has become a
commodity for large parts of societies and new
communication technologies allow ubiquitous access
2.1 The Smartphone is the Mass Computer of
the Future
The smartphone with its sensors, connectivity to
communication infrastructure and availability acts in
the same time as device collecting information and
providing the access to content and services that run on
the web. Smartphones not only allow an almost
unlimited access to information in the web but also
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
give access to services which are not only personalized
but also take a further context such as location or time
into account. New sensors like cameras, microphones,
accelerometers, GPS sensors etc. come along with a
smartphone and the functionalities are expanded with
each generation of hardware. This paper analyses the
possibilities how the smartphone technologies can be
applied in the travel insurance context.
booking a trip and it covers exactly the duration of that
trip. Travel insurers have streamlined their products to
the needs of the third party distribution channels.
Products of different providers are quite similar
providing about the same benefits of coverage. The
processes of fulfillment and underwriting are
downsized to make distribution for the partners as
convenient and simple as possible.
Therefor travel insurers are highly depending on
their distribution partners. The dependency even is
aggravated by the fact that people purchasing travel
insurance are not aware from which travel insurance
company they are purchasing the product. This
dependency has brought the third party providers in a
favorable position for dictating commissions for sales
efforts and lead falling profits for travel insurers on a
long term perspective.
2.2. The Technology Push
Smartphones have a significant impact on the way
customer’s access information. The ubiquitous access
to services via the internet becomes a routine for the
majority of the users, especially when travelling and
staying away from home or workplaces. From insurers
point of view similar situation has arisen as in the early
days of the internet. While the new technology is
hyped by early adopters first success stories of
innovative applications of this technology are
spreading. Travel insurers and insurers in general do
not belong to the early adopters of new technologies.
Based on successful applications in different business
field many companies ask themselves weather this
technology should be adopted and if yes how the
technology should be integrated into the existing
business model and the subsequent value proposition.
Customers’ demand for standardized and affordable
insurance products that are combined with value-added
services grows [6]. On the one hand, the Internet
allows comparing insurance offerings at marginal
search costs. On the other hand it enables customers to
effect insurance contracts with little effort in an
anytime-anywhere manner. Consequently, a growing
number of insurance customers compares and
purchases insurance plans online. Amongst other
reasons, the easy access to competitive offerings and
internet comparison services leads to increasing price
sensitivity and decreasing customer loyalty.
In 2007 the South African insurance company
Metropolitan has created Cover2go [7] accidental
death and funeral cover for the lower income market
using non-agent based distribution channels. During
holiday periods many South Africans who work in the
cities travel far to spend time with their families.
Common means of transportation are minibus taxis
which have a high accident fatality rate. In order to
purchase an insurance policy the new clients only have
to send an SMS with his name and national identity
number to a premium rated short code. By
confirmation of an message of Metropolitan the
contract is concluded and the premium is deducted
from the prepaid airtime on the policy holder’s cellular
phone. This service allows Metropolitan to set up sales
points virtually everywhere and offer access any time.
In a Japanese consortium consisting of the insurer
Tokio Marine and the mobile service operator NTT
Docomo provide the “One Time Insurance” coverage
[8]. One time insurance is designed to provide needed
coverage on a 24/7 basis. Purchases can be completed
via the smartphone with some keystrokes. The
premium is added to the mobile phone bill. The pricing
considers the buying patterns of mobile phone users
who are often led by the impulse to by a relatively low
priced service immediately.
Distribution is supported by a location based
recommender system. Since the providers do know
were the owner of a mobile phone currently is location
and situation tailored offerings can be pushed to the
clients. For example the system recommends travel
insurance at airports and other pre-defined target
locations. But the providers go even further. Based on
an activity log specific behavior patterns are
recognized. This allows not only to predict user
3. Technology Impact on Travel Insurers
Value Chain
A simplified Value chain of a travel insurer
comprehends the steps of distribution, after sales
services and claims management. The impact of up to
date technologies on this value chain is examined in
the next section.
3.3 Smartphone as a New Distribution Channel
Travel insurance providers heavily rely on the
distribution via third party providers such as travel
agencies or online travel portals. Temporary travel
insurance usually is bought as an add-on product when
12
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
activities in the near future but also to provide timely
and useful information to mobile phone users.
emergence of information technologies and the
introduction of claims management systems insurers
industrialized their processes and cut the costs to
administer their claims dramatically. Maas [10]
showed that insurance companies consider the
industrialization of their internal value chain and
processes as the most important strategic challenge for
the years to come. However the first wave of
industrialization affected mainly the internal way of
processing information but left the interface to the
customers untouched.
Emerging technologies as in the field of ubiquitous
and mobile computing drive innovation in claims
management and can ultimately enable cost savings for
insurers. Many customer-facing innovations will help
to differentiate from competitors and enable increased
service levels. But the growing adoption of smartphone
technologies improves the control over claims
management processes.
3.4 Technology application in after sales
services
In the insurance industry travel insurers were
amongst the first to offer value added services
complementary to the existing travel insurance core
products. Travel insurers are said to be the inventors of
assistance services as they realized that travellers face
problems in case of an incident which go beyond the
need of a swift reimbursement of the financial damage.
In case of an incident travellers were often choosing
inappropriate and costly solutions to solve their
problems. These assistance platforms assist customers
whenever and wherever facing problems. These
services platforms were built up on basic
telecommunication technologies such as telephone and
fax. The running of the platforms on a 24/7 basis
makes assistance services cost intensive and difficult to
operate since the resources of the call centers have to
be up- and downscaled according the seasonality of the
traveling behavior. Assistance platforms are passive
standby units waiting for the client to call. The
intervention can be executed only after an incident has
happened and often is more focused on regulating the
access to the insurance benefits than on the salvation
of the client’s issues. For these reasons preventive
interventions to eliminate risks are difficult to
introduce both from an operational and economic
perspective.
Baecker [11] analyzed potential innovations of the
claims management process with the help of mobile
smartphone applications. He identified process
innovations both on the operational and on the
management level. Improvements on an operational
level are based on a timely notification of a loss, the
collection of extensive data related to the incident,
improvements in the quality and the completeness of
the gathered data or the reduction of media breaks.
The implementation of customer feedback in the
processes handled by the mobile device has a
significant impact on the management of processes and
partners. To assess the effectiveness the claims
management process, the response rate of feedback
requests can be measured.
Based on mobile technology and the integration
between mobile devices and enterprise systems,
insurers can request customer feedback after the claim
settlement by leveraging the mobile communication
channel. The feedback embraces a customer’s overall
satisfaction with the claims management process, but
also his rating of services provided by business
partners such as repair shops or towing services.
Feedbacks generated along the process are of high
interest for insurers in order to raise customer
satisfaction.
The Canadian travel insurance branch of Zurich
insurance company introduced a service called
Nomadz illustrates how mobile technologies augment
the assistance services [9]. Nomadz provides services
such as travel, health and security alert advisories, as
well as country and city destination information. The
traveling employee receives the latest alerts which are
relevant to his current location. Based on the travel
route also alerts concerning the chosen destination are
pushed to the employee. The employee can also
retrieve information on their destination country or city
through the Nomadz application. Technologies like
smartphone application, web service, itinerary travel
services and locating abilities are linked together. The
proactive services are backed up with the classic
assistance services mentioned above.
4. Conclusions
The cases have shown that the Internet of Things
and new communication technologies do have a
significant impact on the way travel insurers deliver
3.5 Technology impact on claims management
The claims management process is often referred as
the moment of truth when the insurer can proof his
capability to satisfy customer expectations. With the
13
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
services to their customers and design the business
processes.
Smartphones act as distribution channel which
reveal new dimensions in place and time of selling
using the potentials of context specific offerings.
Product and service offerings may also be adjusted to
these new dimensions as well as the pricing.
Addressing these dimensions mobile technologies do
have a positive impact on sales. Furthermore the new
ways of distribution can offer a strategic alternative to
the dependence in distribution on third party providers
such as travel agents and online travel portals.
On the other hand also the cost side of travel
insurances can be addressed by mobile technologies.
Proactive services such as early warning messages
pushed to the client by the travel insurer reduce the
number of claims. The smartphone makes it simpler
for customers and insurers to get in touch with each
other when they are confronted with an incident. Early
notices of incidents enable effective interventions and
lower the average costs per claim. Last but not least
process automation and reduction of transaction costs
cut down the expenses for administration.
entitled to make use of these assistance services in case
of an incident. Therefore the interaction with the
insurer is limited to the claims scenario. This business
model restricts the market potential only to a limited
number of existing clients.
Mobile technologies can help to turn this business
model upside down. Information can be processed and
distributed very efficiently due to the automation of
processes and very low transaction costs. Services like
a security alerts are pushed to an almost unlimited
number of clients at lowest costs. Potential clients may
are invited to test these services. They can make use of
the services for free and get in touch with the insurers
brand. The users of an early warning system get a
positive brand experience by using these services.
Many popular services in other industries are built
successfully on this so called freemium business
model. Unlike in the existing business model where
access to services is limited to existing clients and the
claims event a large proportion of the potential market
can be addressed in the new model. The attracted
customers can be converted into paying insurance
clients with appropriate marketing activities.
4.1 Limitations
6. References:
New communication channels and information
technologies have evolved and established themselves
recently. As the past has shown it takes quite a long
time until they are fully adopted by the buying
customer. In the travel insurance business it took more
than ten years until the internet sales channel gained an
major share as a distribution channel as the results of
Mondial [2] show. The use of internet based services
in order to access after sales services or claims
settlement is still underdeveloped. Although the use of
smartphones and ubiquitous access to internet services
becomes a commodity in many markets the use of
similar services as described in this paper will show
rather slow adoption rates.
[1]
History
of
Travelers,
http://www.travelers.com/about-us/flash/history.html
[2]
Mondial
Assistance,
Buchungsund
Reiseverhalten der Schweizer Bevölkerung, Umfrage
2009,
http://www.elvia.ch/firmen/images/Studie_Buchungs%20Reiseverhalten_CH_2009.pdf
[3] A. Bereuter et. al., Erhöhte Sehschärfe Technologiebasierte
Innovation
in
der
Versicherungswirtschaft,
Accenture,
www.accenture.ch. 2008
5. Outlook
[4] E. Fleisch, What is the Internet of Things? An
Economic Perspective, Auto-ID Labs White Paper,
www.autoidlabs.org, January 2010
New information technologies may change the
existing business model fundamentally on the long run.
As we have seen in today’s business model travel
insurers offer low differentiated products via
distribution channels in the control of third party
partners. In the search of ways to differentiate from
competition the travel insurance provider may offer
additional services to his clients such as assistance in
case of emergency. These additional services are
tightly linked to the travel insurance products. Clients
who have bought a travel insurance product are
[5] M. Loukides, What is data science, O’Reilly
Radar, 2010
[6] S. von Watzdorf and A. Skorna, How value
added services influence the purchasing decision of
insurance products. World Risk and Insurance
Economics Congress 2010. Singapore.
14
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
[7] A. Smith, H. Smit, Case Study: Metropolitan
Cover2go, www.cenfri.org, July 2010
[8] T. Makino, Providing New Customer
Experience Using Mobile Technologies, I-VW
Trendmonitor 4.2010, November 2010
[9] Nomadz, A mobile
www.getnomadz.com. 2011
Zurich
Helppoint,
[10] P. Maas, B. El Hage, and A. Weigelt.
Industrialisierung in der Versicherungswirtschaft: Eine
empirische Studie in Deutschland, Oesterreich und der
Schweiz. (P. Maas and G. Berner). St.Gallen,
Switzerland: Institute of Insurance Economics. 2007
[11] O. Baecker, Mobile Claims Management: ITBased Innovation in Motor Insurance, Dissertation no.
3809, Harland Media, Lichtenberg. 2011
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Wireless sensor network for disaster prevention of tunnels built by New Austrian
Tunnelling Method
Ruzena Chamrova
Swiss Federal Institute of Technology
MAS MTEC
Raemistrasse 101, 8006 Zurich, Switzerland
[email protected]
Abstract
The safety of tunnels during their construction is an important issue. Tunnel collapse might often result in remarkable consequences, such as casualties, large recovery costs
and substantial delays. It is essential to continuously monitor the tunnel during its construction phase. In this paper
we propose a real-time monitoring system for tunnels constructed using the New Austrian Tunneling Method (NATM).
The new system is presented as an alternative to the current
manual convergence measurement, which is labor intensive
and cannot provide continuous monitoring. The new system
is based on a Wireless Sensor Network (WSNs) comprising of a set of sensors and actuators. The sensors measure
the displacements in- and between the tunnel cross sections
and communicate them to the base-station. An expert system evaluates the information and activates the actuators in
case of acute danger. Technical and business aspects of the
solution are discussed.
1. Introduction
In the night of 20th October 1994, a section of a tunnel constructed at Heathrow airport collapsed. Eventhough
there were no casualties, the recovery cost was 150 million £ and there was a 6 month delay to the project, which
was a part London Jubilee Line Underground extension [5].
A similar case happened in Barcelona (2004), where thousands of people had to be evacuated from the district El Carmen, just above the tunnel, where ground subsidy occured.
Both tunnels have been built by New Austrian Tunneling
Method (NATM) [10], which is the most common method
for building small and medium size tunnels. Yet the collapse cannot be attributed to the method itself but rather
to a lack of early warning and subsequent measures. The
leading idea of the method is ’Design as you go’, i.e. the
final design of the tunnel is not known at the time of the
construction and a set of measures is prepared and used in
case of excessive deformations. Monitoring of the tunnel
is an essential part of NATM, because it can either prevent
the collapse of the tunnel or at least serve as an evacuation
warning.
Recently, wireless sensor networks have been on its rise
thanks to the decreasing cost of hardware, sensing and communication technology [11]. Thanks to this availability they
present an attractive solution for monitoring of transportation structures. This is also the motivation for the business
proposal presented in this paper - a disaster prevention wireless sensor network for the construction phase of NATM
tunnels.
2. State of the art
2.1. Primary lining
The biggest interest during the construction phase of the
tunnel lies in the deformations of the primary lining. Primary lining is a relatively thin layer of sprayed concrete
(shotcrete), which is in direct contact with the rock. It is
usually installed just after a tunnel section is excavated. The
deformations of the primary lining are usually the highest
just after it is installed and in time follow a convergent trend.
Eventhough primary lining is not visible when the tunnel is
operational, it is the crucial part of the tunnel during the
initial phase of construction. This is when the system is at
its weakest and monitoring of its deformations is crucial for
safety and disaster prevention.
2.2. Conventional monitoring method
One of the most common monitoring techniques which
can indicate a possible threat of a collapse is a contactless
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
convergence measurement [2]. The tunnel is analysed in individual cross sections, which are regularly spaced (usually
5-30 m based on geological conditions). Each cross section contains a set of convergence bolts set in the shotcrete
with a bireflex target (mirror) [2], Fig.2. These bolts are
the reference point for measuring deformations by a laser
tachymetry and usually there are 3 or 5 of them per cross
section (based on the size of the tunnel), Fig.3. Laser
tachymetry is performed for each section individually by
a surveyor equipped with a laser tachymeter. The surveyor
targets the mirrors of the convergence bolts with the laser.
The measurement allows to reconstruct the deformations of
the tunnel as the construction progresses.
Three important trends need to be captured - the deformation of the cross section, the horizontal and vertical displacement. The deformation of the cross section can be
obtained based on the mutual distances of the convergence
bolts in a cross section. For horizontal and vertical displacement the surveyor needs to connect to the previous cross
section of the tunnel. One cross section measurement takes
∼ 5 minutes. The measurements of the cross section are
performed once per day, but only in the first three days after
excavation. Once a convergent trend is visible, the interval
between measurements increases (5, 7, 14, 28th day). The
intervals are a result of a long-term experience. The measurements often have to be scheduled so that they do not
interfere with excavation and construction work.
Yet, performing the measurements in the abovementioned intervals is often insufficient in case of nonconvergent trends. It can lead to misinterpretations of the
data and wrong conclusions regarding the measures. Moreover, as the measurement is conducted only for the sections
close to the excavation face, it is hardly obvious how the
tunnel behaves along its length. This can become important, when another civil engineering structure is close-by
(another tunnel, buildings on the top of the tunnel etc). All
in all, there is certainly room for improvement in the conventional system, especially in the ’real-time’ disaster prevention domain.
2.3. Wireless sensor networks in tunnels
Wireless sensor networks can be used in tunnels both
to ensure safe construction and enable smooth operations.
Compared to standard wired electronical systems, WSNs
offer several interesting advantages. Especially in dynamic
environments, they can be easily deployed as they do not
rely on existing infrastructure. WSNs by design provide
redundancy to tolerate operation under harsh conditions,
i.e. they do not suffer from an accidental disconnection.
The maintanance of WSNs is somewhat easier as only standalone nodes have to be serviced, instead of a general overhaul of the entire system.
Up to now, wireless sensor networks in tunnels have been
mostly deployed for operational purposes. Currently their
use include monitoring of the deterioration of the tunnel
lining [4] and controlling the light intensity in tunnels [1].
While fire disaster relief is of great interest [8], the system
is still far from being deployed. To the best knowledge of
the author, a wireless sensor network has not been yet deployed during the construction phase of the tunnel, eventhough there had been some research going on for mines
[6].
Tunnels constitute a special environment for WSNs,
when compared to more traditional deployements as the
shape of tunnel acts as a waveguide allowing communications over a longer distance than normally possible. This
has both advantages and disadvantages and has drawn interest of the research community [7].
3. Disaster prevention solution during construction of NATM tunnels
3.1. Vision
A ’real time’ disaster prevention system for the tunnel
construction would ideally work in four stages:
1. sense the deformations in the cross sections
2. communicate the deformations through a WSN
3. evaluate the deformations along the tunnel
4. actuate alarms in case of excessive deformations or
non-convergent trends
In the following, such a disaster prevention system will
be presented and discussed with regard to the requirements
and possible limitations.
3.2. Deployment
The deployment of the WSN in the tunnel is closely connected to the excavation cycles. Once a section of the tunnel
is excavated and the shotcrete layer is constructed, a node
of the WSN is deployed. This node automatically connects
to the base station at the beginning of the tunnel. As the
construction progresses, more and more nodes with the selforganization capability are deployed, Fig.1.
More denser deployment might be needed for tunnel portal, junctions or close to excavation face. As excavation
face moves further away from the problematic cross section, a lower density of nodes becomes sufficient and the
redundant nodes can be removed without any change to the
system.
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Figure 1. Disaster prevention system in a NATM tunnel (longitudinal section)
3.3. Sensing
The purpose of sensing is to obtain mutual distances of
selected points in the cross section and their displacements.
In order to do so, a device capable of measuring distances
is needed.
In the conventional system this requirement is represented by a laser tachymeter operated by a surveyor. The
surveyor is usually standing approximately in the middle of
the tunnel and has to move the device everytime a measurement of a new cross section is required. In the proposed
system the laser tachymeter is replaced by a distance sensor
node located on one of the walls of the tunnel. Unlike the
surveyor who has to move, each cross section has its own
sensor node, Fig.3.
The required measurement accuracy of the distance is ∼
1mm. The most common methods capable of achieving this
accuracy is laser ranging and ultrasonic ranging. The sensor node will be equipped to perform continuous distance
measurements between the node and the reference points
attached to the shotcrete lining.
Figure 2. Convergence bolt (left) with a bireflex target-mirror (right)
Figure 3. Disaster prevention system in a
NATM tunnel (cross section)
municated in regular intervals (0,5 hours sufficient). which
represents the sampling frequency of ∼ 0.001 Hz. This
qualifies for a very low frequency communication and thus
poses no significant challenges in terms of energy consumption [3]. Moreover, the radio of the node does not communicate when there is no change in displacement. In case
of a node failure in a particular cross section, the network
can reroute the information through the further cross section. The expected communication range of a typical WSN
node in a tunnel environment is known to exceed 100 m,
which is sufficient to provide the required communication
redundancy in this project.
3.5. Evaluation of the deformations
3.4. Communication
The communication in the tunnel is accomplished
through node self-organization. The displacement is com-
Postprocessing of the acquired data is performed on the
node (to save communication energy) as well as in the base
station outside of the tunnel. An expert system is responsi-
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
ble to check for the anomalies along the tunnel, which are
acquired from the evaluation of the displacements and convergence trends in the individual cross sections. A visualisation software helps to highlight the type of problem faced
and enables to take the correct measures.
• development cost of the expert system, visualisation
software and sensing technology
3.6. Actuation of alarms
• operational variable costs based on the duration of the
construction
Wireless actuator nodes are added to the existing network at 200 m intervals to warn the construction workers
in case of acute danger detected by an expert system. The
acute danger represents a node displacement of 30-50 mm
(based on the geological conditions). The actuator node
consists of an alarm light and a horn and connects to the
existing WSN through standard communication protocols.
3.7. Technical challenges
In order to be successfully deployed, several technological challenges need to be solved. These include improvement of the sensing technology, addressing physical security of nodes, developing expert systems and gaining acceptance in the field.
One of the biggest challenges is the sensing technology.
While distance sensor units exist as off-the-shelve components, a custom laser or ultrasonic sensing unit might be
necessary for the required precision, distance range and environmental conditions (dust, dirt, humidity).
Secondly, physical security of the nodes might pose a
challenge. The nodes are often exposed to water, blasts
from excavations or a damage by tunnel vehicles. Robust
casing is thus essential.
Thirdly, a significant amount of knowledge in the expert
system is required to correctly evaluate the situation and not
to cause false alarms. Cooperation with research groups
might be required.
Last, civil engineering is a traditional field and wireless
sensor networks is a relatively new technology. A significant amount of tests and comparisons to conventional methods will have to be performed before the system can be deployed.
4. Business aspects
Tunnel collapse often represents severe consequences
with regard to recovery costs, delays and company reputation. Last but not least, no money can be put on the value
of the human life. In the following, the business aspects of
the proposed disaster prevention system will be discussed.
The business idea is to make a company which will sell
or lease the full solution for the disaster prevention system.
For this idea to be realized the following costs need to be
considered.
• variable costs based on the length of the tunnel (sensor
and actuator nodes, convergence bolts with targets)
The development cost for the sensor nodes, expert system and visualization software is estimated to be 5 man
years of work, thus represents ∼ 500’000 CHF.
Cost per one sensor and actuator node can be estimated
from the price of a prototype which could be made out of
off-the-shelf components. The cost of a prototype for a sensor node is expected to be in 1’000 - 2’000 CHF range.
According to my estimations ∼ 70% of the cost could be
attributed to the distance sensing unit. With the mass production the cost is expected to drop into the range of 500 1’000 CHF.
The cost of the prototype of the actuator node is expected
to be ∼ 500 CHF, while the mass production costs are expected to be between 150 - 250 CHF.
The cost of convergence bolts with targets per cross section is ∼ 150 CHF.
Operational costs represent one fully employed person
throughout the duration of tunnel construction. Under the
assumption of no delays and a speed 3m/day that would result in ∼ 100’000 CHF/year.
The cost for 1m of a tunnel constructed by NATM varies
between 10’000 and 90’000 CHF [9]. The variable costs
of the disaster prevention system based on the length of the
tunnel would be ∼ 50 CHF per 1m of tunnel and thus constitutes max of 0.5 % of the total tunnel cost.
It is expected that the system will be sold and leased to
multiple tunnel constructions, thus the development costs
can be retrieved through several projects as licensing fees.
5. Conclusions and next steps
In the paper, we presented a disaster prevention system
for the construction phase of NATM tunnels. The wireless
network comprising from sensor and actuator nodes would
act as a real-time monitor for non-convergent trends and
excessive deformations and would allow to warn the construction workers in case of acute danger. Technical aspects,
challenges as well as business aspects were presented.
Before the system can be rolled out, several major issues
need to be addressed further. The first of them is the development of a sensor prototype. This involves testing of the
prototype on a few tunnel cross sections in different conditions. Results of this should then be compared to the traditional measurement. Secondly, thorough tests of the whole
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WSN are needed with regard to the sensing, communication and environmental exposure. This phase would require
high cooperation from the tunnel personnel. Last but not
least, development of the expert system is necessary. This
phase is critical for the correct danger identification and requires the support of the research community. Provided all
these issues are addressed, I believe the system can be successfully deployed in NATM tunnel construction.
References
[1] M. Ceriotti et al. Is there light at the ends of the tunnel?
wireless sensor networks for adaptive lighting in road tunnels. In 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN/SPOTS), April
2011.
[2] GIF. Convergence measuring instruments. http://www.gifettlingen.de/engl/html/geotechnical instruments.html,
retrieved 13.4.2011.
[3] M. Hempstead et al. Survey of hardware systems for wireless sensor networks. Journal of Low Power Electronics,
4:1–10, 2008.
[4] N. Hoult et al. Wireless sensor networks: creating smart
infrastructure. In Proceedings of ICE Civil Engineering 162,
pages 136–143, August 2009.
[5] HSE. Collapse of natm tunnels at heathrow airport. a report on the investigation by the health and safety executive
into the collapse of new austrian tunnelling method (natm)
tunnels at the central terminal area of heathrow airport on
20/21 october 1994. Technical report, Health and Safety
Executive, 2000.
[6] L. Mo et al. Underground coal mine monitoring with wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5:10:1–10:29, April 2009.
[7] L. Mottola et al. Not all wireless sensor networks are created
equal: A comparative study on tunnels. ACM Transactions
on Sensor Networks (TOSN), 7(2):15:1–15:33, September
2010.
[8] RUNES. Reconfigurable ubiquitous networked embedded
systems. http://www.ist-runes.org/, retrieved 13.4.2011.
[9] TAV.
Brief description of tunnelling technologies.
http://www.tavbrasil.gov.br/Documentacao/Ingles, retrieved
13.4.2011.
[10] L. von Rabcewicz. The new austrian tunnelling method. Water Power, pages 511–515, 1964.
[11] J. Yick et al. Wireless sensor network survey. Computer
Networks, 52(12):2292–2330, 2008.
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Concept for a Basic Soccer Analysis Service
Patrick Haas
Swiss Federal Institute of Technology
Department of Management, Technology and Economics
[email protected]
Kill-a-Watt [1] monitoring device counts your amount
of consumed electricity, the Sleep Cycle [2] mobile
app analyzes your sleep patterns and the Happy Factor
[3] software regularly asks you how happy you
currently are via a text message. Possible applications
are vast, and the amount of products and services
which enable you to log your life steadily increases [4].
From the granular information being now gathered, we
can derive instructive patterns; gain new insights by
data visualization, analysis and comparison. In general
terms, quantitative and qualitative assessment of our
activities leads to an increased awareness of the way
we live our lives. Personal statistics provide feedback,
and the provision of additional information, being
finally accessible, helps us to improve our behavior:
the Kill-a-Watt connector helps us… yes… to kill a
watt (or even more than one), i.e. it supports the
reduction of energy consumption costs with a simple
cumulative Kilowatt-Hour monitor. The sleep cycle
app determines our sleep statistics and wakes you in
the lightest sleeping phase; for a pleasant start of the
day. Happy Factor enables us to “learn how to have
more happiness” [3] in our life.
Abstract
People more and more track and quantify
themselves and their activities. The trend is enabled by
new technologies and tools, making it trivial to
aggregate data. Subsequent analysis derives
instructive patterns and helps us to improve our
behavior. The clear purpose of performance
improvement makes tracking systems also common in
sports, where athletes act as pioneers in the field of
self-quantification. Even in soccer, coaches and
players become increasingly aware of the power of
statistics for performance assessment. Several highend tracking systems and performance analysis
services are available, but are too sophisticated and
expensive for the large market of ambitioned amateur
teams. To fill this market gap, I propose a concept for
a basic soccer analysis service at comparatively low
cost. The service uses GPS devices to track players
during practice and provides a post-game performance
analysis. The aim is to optimize game preparation and
training methods resulting in a competitive advantage.
Scientific studies which quantify and analyze
Australian Football League player demands during the
last years serve as a basis for the proposal.
2. Monitoring Systems Conquer Sports
1. Introduction
2.1. Pioneers and Commercialization
“All is number” was the vision of Pythagoras, a
Greek philosopher and
mathematician.
The
interpretation of the sentence remains vague, but it
accurately describes a new and all-pervasive meta
trend. People are excited to track their activities and to
break them down into numbers; they gather and
evaluate data about themselves. How high is my
current energy consumption at home? How many hours
of sleep did I get last week? Or even: How did I feel
during the day, rated on a scale from 1 to 10? Today,
new technologies and tools provide answers in a highly
convenient way. Tracking yourself is trivial now and
this is boosting the trend of self-quantification. The
Few areas of human activity illustrate the trend to
quantify better than sports. “Athletes have kept training
logs to quantify and analyze” [5] their activities, i.e.
their workouts. Systems to record and evaluate
“physical movement and physiological response to
exercise” [6], such as video analysis software and heart
rate monitors are common among professional
sportsmen. They are pioneers in the field of selfquantification. The widespread use is based on the
obvious purpose of self-tracking in professional sports:
to increase performance. The power of data
monitoring, analysis and feedback provision supports
the achievement of this goal. Scientific investigations
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
and national teams also rely on performance analysis
tools to optimize their game preparation.
“People in soccer have historically paid little
attention to statistics” [18]. Also, there is a general
attitude against technology directly influencing the
sport. A fear that technology might ruin soccer is
noticeable and illustrated by the long-lasting discussion
about the implementation of a goal detection system.
Nevertheless, the power of numbers is also slowly
taking over the so called “beautiful game”. Staffs and
coaches start to recognize the benefits of analytics in
soccer [18] [19]. But data capturing and analysis soon
becomes difficult and the comprehensive approach of
current service providers makes systems and services
expensive – and therefore exclusive.
confirm that performance and skill acquisition tends to
increase when relevant feedback is provided in an
appropriate manner [7]. Therefore, systems which
accurately monitor data and provide proper feedback
clearly deliver value to athletes.
The commercialization of tracking systems let the
trend of self-quantification spread among the whole
sports community, including the mass of amateurs.
Very popular examples are tracking systems for
runners from large sport equipment suppliers (Adidas
[8] or Nike [9]) or specialized companies like Fitsense
[10], Fitlinxx [11], and many others. Depending on the
product, these systems integrate one or more sensors to
measure running distance, pace, heart rate and location
of the athlete and provide real-time feedback as well as
possibilities to visualize and evaluate your data after
workouts. Beyond pure data visualization and analysis,
product-augmenting services like the possibility to
share and compare the gathered data among an online
community emphasize the social and fun dimension of
sports and tailor the product to the hobbyist‟s needs.
Sharing and comparison enrich the sports experience
and make it more tangible and enduring.
Numerous examples can also be found in less basic
forms of individual sports. Applications are not that
popular (yet), but cover a wide range from golf [12] to
tennis [13].
2.3. What About an Affordable Solution?
Usual prices range from € 20‟000 to € 100‟000 [20]
per season for currently available analysis services and
are therefore only affordable for professional soccer
clubs. Less expensive offerings for adapted services
targeting the market of ambitioned amateur clubs are
rare. Statzpack [21] offers one of the most basic
solutions: a simple iPhone app for easy manual entry
of soccer statistics during a game, not considering
automatic capturing technologies. Following the
simplest approach, it nevertheless provides value to
coaches and players. In the area of low cost football
analysis tools, German-based Master Coach
International markets a stand-alone video editing
software named PosiCap [22]. Some similar competing
products are on the market.
Previously, there have been implications that the
development of “a relatively cheap football analysis
tool” [23] would meet positive market conditions, at
least in northern Europe. Considering also the recent
development in the market of running and an emerging
positive attitude towards monitoring systems in the
soccer community, one can conclude that an increasing
market potential for solutions to quantify and evaluate
soccer performance at low investments is present.
Competitive amateur level teams are interested in
investing in technology for performance enhancement.
This encourages the development of a respective
concept, as presented in this paper.
2.2. Few and Expensive Systems for Soccer
“Team sports have probably been the most difficult
sporting area to [quantitatively] assess” [6], due to the
sheer number of players, their complex interactions
and the different positional demands. Focusing on
soccer (this is European football for the rest of the
world; I call it like this to better differentiate it from
Australian football), there are only few commercial
systems and services on the market: mainly high-end
solutions from premium suppliers. Impire [14], Amisco
[15], Prozone [16] or Match Analysis [17] provide
comprehensive performance analysis systems and
services with individual player tracking and a mass of
positional and physical information for live or post
match analysis. Video footage from up to twelve
cameras is combined with data captured by scouts:
people who precisely observe the game and record
additional statistics such as touches, passes, tackles,
fouls, shots, goals, cards and more. Deliverables range
from simple graphical representation of data (e.g. pace
of a player during gameplay) to 2D and 3D animation
of in-game situations. Customers are television
channels and other news organizations which augment
their sports coverage. More recently, top soccer clubs
3. Concept for a Soccer Analysis Service
3.1. Using AFL Research as a Basis
Extensive investigations into the physical demands
of playing Australian Football League (AFL) have
been carried out since 2005 by Wisbey et al. [6] [24].
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
shorter distances at high speed” [24] when applied to
AFL movement patterns. I assume that errors are of
similar order when devices are applied in soccer sports.
Especially for sprinting distances, further development
has to be considered to reduce errors.
The fact that the GPS tracking systems are
extensively used in Australian Football, a full-contact
sport, implies accurate wearing comfort, no increased
risk of injury and no or only marginal influence on
player agility.
The research is based on GPS data collected in both
game and training environments. GPS has proven to be
an effective means of player tracking for outdoor team
sports [6]. Other researchers conclude similar results,
but also show limitations in the “assessment of short,
high speed straight line running and efforts involving
change of direction” [25]. As training benefits from
player workload statistics are recognized, GPS devices
are now extensively used among all sixteen AFL
teams. The systems record positional variables and
speed. From the collected data, several performance
indicators are determined. The present concept
partially adopts ideas, approaches and conclusions of
the work of Wisbey et al. But while these researchers
conducted scientific studies as a project funded by the
AFL Research Board, I aim at defining a commercial
soccer analysis service.
3.4. Core Service
The only thing players of a customer‟s team have to
do is to wear the GPS devices. After the match or the
training, they return the devices to the service provider,
which downloads the data and imports it to a custombuilt analysis software. The steady state and movement
pattern variables are computed from the data files and
are listed in table 1 and 2. All analysis is done after the
end of the recording. No analysis in real-time is
provided, because this would require additional
moveable infrastructure and therefore increase cost.
3.2. Proposal
I am proposing a solution to provide a soccer
performance analysis system for clubs with ambitioned
amateur or semi-professional teams or for clubs which
professionally promote young talents. The target group
is characterized by the common need for a tool to
accurately assess a player‟s performance demand
during game play. The aim is to optimize game
preparation and training methods resulting in a
competitive advantage. At the same time, investment
capabilities of possible customers are constrained; high
end solutions from premium suppliers are not
affordable. The way the target group is approached is
therefore the delivery of a basic soccer analysis
service, comprising a monitoring system with reduced
complexity. In an overall growing market of products
assessing performance in sports, the service addresses
the almost “untouched” market segment of ambitioned
mass sports in soccer, assuming an evolving business
potential. Being aware of the limitations of the
monitoring system, the focus lies on the provision of a
clean and valuable performance analysis, which
delivers immediate benefits to the customer.
Table 1. Analysis variables for work profile
Work Profile
Total Distance
Average Speed
Total Time
Exertion Index
Exertion Index per Minute
Units of Measurement
km
km/hr
mins
/mins
Table 2. Analysis variables for movement
pattern profile
Movement Pattern Profile
Time Spent in Speed Zones
Longest Continuous Time
Above a Specified Speed
Surges Above/Below a
Specified Speed
Number of Accelerations
3.3. Monitoring System
Number of Decelerations
To minimize costs, the monitoring system
deliberately omits the setup and operation of camera
systems and the evaluation of visual data. The data
sensing unit is a commercial GPS device, fitted to the
upper back of each player using a harness, similar to
the configuration of Wisbey et al. The devices record
speed, altitude, latitude and longitude at 5 Hz
throughout the duration of practice and store the data
internally. The sampling rate results in a GPS error
ranging “from 2% for long distances up to 5-20% for
Units of Measurement
s
s
# times >/< x km/hr (x to be
defined)
# Accelerations > x km/hr in
1s (x to be defined)
# Decelerations > x km/hr in
1s (x to be defined)
Table 1 and 2 take over most of the variables from
investigations of Wisbey et al. Definitions of the
variables are given in the appendix. The values
accurately describe AFL player workloads and are a
reasonable first choice to evaluate soccer player
demand. Running distances and moving patterns of the
two sports are similar to a certain degree. Nevertheless,
further investigations have to be undertaken in order to
verify this assumption. Of special interest is the
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
exertion index, an estimate developed by Wisbey et al.
“to quantify the level of physical work completed by
players”. Combined with the exertion index per
minute, which serves as a measure of game intensity,
the two variables clearly provide deeper insight in the
physical challenges of soccer.
Each data file is associated with information about
the player (position, team, etc.) and the game
(exhibition or championship game, opposition, type
and dimensions of pitch, date and time, etc.). The
analysis is done on the level of players, but can be
consolidated for position, group or team evaluation.
Provision of processed data happens via a web
interface. A login function distinguishes different
users. Depending on their user role, coaches, staff and
players can look at different levels of the analysis. As a
default, players might only be able to access their own
data and the statistics they are involved in, and coaches
can look at the complete analysis. Simple charts and
tables, but also more sophisticated visualized analyses
are provided. Examples, illustrated with figures 1, 2
and 3, are: (1) histograms of Exertion Index levels, (2)
pie charts representing the distribution of Time Spent
in Speed Zones across different positions and (3) heat
maps, which graphically represent a player‟s positional
variable for a whole game. In addition, 2D illustration
of the movement of the back four, the midfield or the
forward line could be presented. Various ways of data
processing and visualization are possible, and the most
beneficial and educational analyses have to be
evaluated with possible customers before product
launch. Insights into physiological demands, but also
into tactical behavior of players and of the whole team
enable implications for training methods and game
preparation. In addition, an increased awareness of the
behavior on the pitch is likely to lead to an adaption
and improvement of the player‟s performance.
Figure 2: Pie chart showing the distribution of
Time Spent in Speed Zones across positions
[6]
Figure 3: Heat map [27]
Interfaces to social networks enable players to share
their personal statistics with others, if they want to do
so. A distribution functionality enriches the sports
experience, as illustrated by the tracking systems for
runners. Sharing the soccer performance data among
an online community reinforces the experience by
making it comparable, tangible and enduring. This
effect creates considerable additional value.
The possibility to compare personal data with
figures of top-level players might also be of great
interest, especially for young players. For the moment,
comparison is mostly limited to the distance covered
during a game, since no other values are normally
provided during TV broadcasts of soccer games. For
certain important international games, additional
statistics are provided in the internet [27] [28].
3.5. Offers for Service Packages
Since one-time data capturing makes little sense
due to lack of comparable data, the service is generally
provided in packages. The customer can buy the
evaluation of three distinct units (trainings or games)
during the preparation phase for the championship,
focusing on the progress of individual players. Another
package including the evaluation of five or more
successive units illustrates the development of player
fatigue and helps prevent injuries. Further
configurations are possible.
Figure 1: Histogram representing total
Exertion Index across all positions [6]
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
provided to date, but will considerably influence the
long-term success of the proposed service. To
maximize probability of success, early prototype
deployment and customer involvement is important.
3.6. Additional Services
Additional services extend the core service and
might or might not be included in a service package.
Additional consulting as a “follow-up service” serves
as an example. Starting from the findings of the initial
analysis, the service supports the development of
tailored training methods and preparation scenarios
before a game. Cooperation with medical specialists
and the experience of the service provider thereby
leverage the results of the core service.
4.2. Opportunities
Considering the tracking devices, combined
accelerometer/GPS units could offer a greater accuracy
and resolution in data capturing. In addition,
development in sensor technologies, Local Positioning
Systems and Near Field Communication technologies
could soon completely replace the GPS system. The
GPS devices, being a drawback because of their size,
might therefore soon become redundant. As long as the
new technology provides similar or even more accurate
data, the service quality is not affected. Of course, such
technologies come at considerable cost, which have to
be evaluated in advance.
The service follows a basic approach and is
therefore easily extendable. Once the technology is
accepted (and maybe also allowed in official games)
and benefits are shown, product and service
development in various directions is possible.
3.7. Price and Promotion
The price range for the service packages is clearly
below the one of premium suppliers, who charge
between € 20‟000 and € 100‟000 per year for the
system and for data evaluation [27]. The focus on postmatch analysis, together with the abandonment of
cameras and video footage keep costs of the service
low. Reusable and only little infrastructure and
relatively low running cost for the service provider
make this assumption reasonable.
Promotion is focused on, but not limited to, shirt
advertising. An initial approach is to provide the soccer
sports analysis service to a team for free. In return, the
team wears jerseys with the advertisement of the
service provider.
Local newspapers or other media might be
interested in data of games of lower leagues and junior
leagues. They are possible customers and have to be
addressed as well to create further revenue streams.
7. Appendix: GPS
Definitions
Analysis
Variable
The following definition are taken from [24]:
Total Distance: Measures the total distance
travelled during the playing period. Measured in
kilometers.
Average speed: Total distance divided by total
playing duration in hours. Measured in km/hr.
Total Time: The total on field playing duration.
Measured in minutes.
Exertion Index: Exertion index is a quantifiable
level of physical load developed by FitSense Australia.
This measure allows a relationship to be drawn
between game load, fatigue, and the total load between
players. The exertion index used to assess GPS data in
this project was based on the sum of a weighted
instantaneous speed, a weighted accumulated speed
over 10 seconds, and a weighted accumulated speed
over 60 seconds. This ensures both short sharp efforts,
and long sustained efforts are analyzed equally. The
weighting is based on a polynomial relationship in
which high speeds achieve a higher exertion value than
lower speeds. Exertion index is measured in arbitrary
units. Please refer to the paper for further details.
Exertion Index per Minute: This is a measure of
game intensity and is determined by dividing exertion
index by playing time.
4. Discussion and Conclusion
4.1. Risks
Currently, wearing technical devices during official
soccer games is prohibited. From personal experience,
I know that regional soccer federations, at least in
Switzerland, can adapt the rules. But if they are able to
allow GPS devices remains unclear. However, first
analyses are constrained to friendly matches, which
might hinder a reasonable market penetration.
It is of course also possible that soccer players do
not accept GPS devices worn during game play. This
uncertainty is present until the launch of the service,
but might obviously prevent the whole concept from
being a success.
The general questions remain, whether the trend of
quantification will further develop and if the soccer
community will finally and entirely accept technology
in the game. Answers to these questions cannot be
25
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
[9] [Online] www.nikerunning.com. Access: 09.04.2011.
Time Spent in Speed Zones: Time spent between
the speeds of x and y km/hr. Provides information on
the dispersion of speed throughout the session.
Longest Continuous Time above a Specified Speed:
The longest period of time the player stays above this
speed, without dropping below this speed. Time is
recorded even when the player enters a higher speed
zone. Provides an indication of the longest continuous
effort at varying speeds.
Surges above/below a Specified Speed: The
number of times the player goes from below (above)
this speed to above (below) this speed. Gives an
indication of the intermittent nature of the session, and
the intensity at which speed peaks occur.
Number of Accelerations: The number of times the
speed increases by more than x km∙hr-1 in a 1 second
time period. This gives an indication as to the
accelerations undertaken and how frequently these
occur. Accelerations are categorized as moderate (4
km∙hr-1) or rapid (10 km∙hr-1).
Number of decelerations: The number of times the
speed decreases by more than x km∙hr-1 in a 1 second
time period. This gives an indication as to the
decelerations required and how frequently these occur.
Decelerations are categorized as moderate (4 km∙hr-1)
or rapid (10 km∙hr-1).
[10] [Online] www.fitsense.co.uk. Access: 09.04.2011.
[11] [Online] www.fitlinxx.com. Access: 09.04.2011.
[12] [Online] www.thegolfsystem.com. Access: 14.04.2011.
[13]
[Online]
http://www.xtremesportsmachines.com/
contents/enus/d31_Xtreme_Tennis_Software.html. Access:
14.04.2011.
[14]
[Online]
www.bundesliga-datenbank.de/de/home/.
Access: 10.04.2011.
[15] [Online] www.sport-universal.com. Access: 10.04.2011.
[16] [Online] www.prozonesports.com/product-prozone3.
Html. Access: 10.04.2011.
[17] [Online] www.matchanalysis.com. Access: 10.04.2011.
[18] T. Kaplan, „When It Comes to Stats, Soccer Seldom
Counts”, New York Times, 08.07.2010.
[19] N. Deleon, “Why are we so afraid of technology
„ruining‟ soccer? It‟s not like technology hasn‟t been all over
the sport since its inception.”, Crunchgear, 03.08.2010.
[20] M. Drauz, “Die Bundesliga im Datenrausch”,
Frankfurter Allgemeine Zeitung, 18.05.2009.
8. References
[21] [Online] www.statzpack.com/overview.php. Access:
10.04.2011.
[1]
[Online]
http://www.p3international.com/products/
special/P4400/P4400-CE.html. Access: 10.04.2011.
[2]
[Online]
10.04.2011.
http://mdlabs.se/sleepcycle/.
[22] [Online] www.mastercoach.de. Access: 10.04.2011.
Access:
[23] D. Setterwall, “Computerised Video Analysis of
Football – Technical and Commercial Possibilities
for Football Coaching”, Stockholm, 2003.
[3] [Online] www.howhappy.dreamhosters.com. Access:
10.04.2011.
[24] B. Wisbey, B. Rattray, and D. Pyne, “Quantifying
Changes in AFL Player Game Demands Using GPS Tracking
– 2010 Season”, AFL Research Board Report, University of
Canberra, Canberra, 2010.
[4] G. Wolf, “Know Thyself: Tracking Every Facet of Life,
from Sleep to Mood to Pain, 24/7/365”, Wired Magazine,
17.07.2009
[5] M. McClusky, “The Nike Experiment: How the Shoe
giant Unleashed the Power of Personal Metrics”, Wired
Magazine, 17.07.2009.
[25] D. Jennings et al., “The validity and reliability of GPS
units for measuring distance in team sport specific running
patterns”, International Journal of Sports Physiology and
Performance, Victoria University, Melbourne, 09.2010, pp.
328-341.
[6] B. Wisbey, P. Montgomery, “Quantifying AFL Player
Game Demands Using GPS Tracking – 2005 Season”, AFL
Research Board Report, FitSense Australia, Canberra, 2005.
[26] P. Gastin and K. Williams, “Accuracy of 1 Hz and 5 Hz
GPS devices to measure movement patterns in team sport
activities.”, Deakin University, Melbourne, 2010.
[7] D.G. Liebermann et al., “Advances in the Application of
Information Technology to Sport Performance”, Journal of
Sports Sciences, Taylor & Francis Ltd, London, 2002, pp.
755-769.
[27] [Online] http://wwos.ninemsn.com.au/article.aspx?
id=830454. Access: 16.05.2011.
[8] [Online] www.micoach.com. Access: 09.04.2011.
[28]
[Online]
http://de.uefa.com/uefachampionsleague/
statistics/index.html. Access: 16.05.2011.
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
The value of “the Internet of Things-mashup” for enterprises
Dominique Mirandolle
[email protected]
they want the data to appear in their own application.
An example is the combination of articles from The
New York Times and Flickr, in which pictures are
shown automatically according to the news by
selecting key words from the selected article.
One specific category of mashups is valuable for
enterprises in specific, namely the business process
mashup [2][3]. Many enterprises invest in large
information systems that serve the overall goals of the
company. However, in a dynamic environment the
need arises for smaller applications for specific
business needs that do not fit in the architecture of the
overall information system. Such business problem
solving applications can also be regarded to as
„situational applications‟ [4], and could in most cases
very well be developed in the form of a mashup. This
tendency supports the need for Service Oriented
Architectures,
where each business process
individually can (re)use specific information
technology services based on their own requirements
[5]. The enterprise mashup in specific can be defined
as “a Web-based resource that combines existing
resources, be it content, data or application
functionality, from more than one resource in
enterprise environments by empowering the actual
end-users to create and adapt individual information
centric and situational applications” [6].
Next to mashups, we elaborate on a second topic in
this paper, namely the Internet of Things. This concept
entails the phenomenon in which every object in our
world can be made „smart‟ by adding a tiny computer
to it with a connection to the internet [7]. By measuring
specific data, for example location, temperature or
altitude, information of value can be obtained from
each „thing‟ and additionally from all the „things‟ in
relation to each other. The obtained data can be used in
numerous ways, and also in the form of a mashup. An
example is the combination of live tracking data of the
public transport in Zurich and Google maps by
local.ch, which creates an overview of the city with
moving trams on a map.
Now that it is discussed what (enterprise) mashups
entail, and how they can come forth from the Internet
of Things, the main question of this paper is proposed
as follows:
Abstract
Mashups appear more and more in the enterprise
domain ever since the need for specific business
applications started to arise. This paper discusses
mashups and more specific their appearance in
enterprises. The second topic of this paper is the
Internet of Things, a phenomenon which entails
„smart‟, internet connected, objects in the physical
world. By bringing these two topics together, it is
described how the development of mashups can be
supported by the Internet of Things and how this leads
to the creation of even more interesting applications.
Additionally, it is discussed what the value of “the
Internet of Things-mashup” can entail for enterprises.
1. Introduction
The mashup is one of the latest concepts to appear
in the Web 2.0 domain. A mashup is “a way to create
new Web applications by combining existing Web
resources utilizing data and Web APIs” [1]. This has
turned out to be especially useful for end users who are
aware of the specific requirements they want an
application to contain. An example of a mashup is the
Microsoft Outlook Social Connector, which combines
data from various social networks (e.g. LinkedIn,
Facebook, MySpace) with your personal address book
in Microsoft Outlook. Numerous mashups exist based
on Google Maps, for example the crime map. This
mashup uses the publicly accessible data from a police
department in a specific area to mark which
neighborhoods are safe and which have a high rate of
crimes. This could even go as far as rating what type of
crime is most likely to appear in certain areas. Instead
of crime rates, maps can also be mashed with for
example data from real estate agents, to show potential
buyers in which areas houses are available.
Since the introduction of the mashup, many
platforms, for example the IBM Mashup Center, have
been developed to make it as easy as possible for the
end user to take part in the „mashing up‟ of various
web sources. Another mashup platform is Yahoo!
Pipes, which offers a graphical interface in which users
can combine various web feeds, web pages or other
web sources through a „pipe‟ and define exactly how
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
In what way can mashups, based on the Internet of
Things, be of any value for enterprises?
By answering this question it is illustrated how
mashups, based on the Internet of Things, can be used
in enterprises. Additionally, some possible future
applications of the usage of these two concepts
combined are described.
This paper is structured as follows. In the second
section related work regarding mashups and the
Internet of Things is discussed. The third part
elaborates on the usefulness of these concepts for
enterprises. Additionally, an example of a future
application is given. Finally, the conclusion
summarizes in what way “the Internet of Thingsmashup” can be of value for enterprises.
to the changing needs of the dynamic business
environment.
Guinard et al. [8] present a resource oriented
approach to develop enterprise mashups while
integrating the Internet of Things. They discuss that
implementing „smart things‟ (e.g. Wireles Sensor
Networks) into an information system requires a
substantial effort and is therefore most suitable for
static environments. However, most enterprises operate
in a dynamic environment. This is the reason why
Guinard et al. propose the Representational State
Transfer (REST) approach, in order to “increase
interoperability for a looser coupling between parts of
distributed applications” [8]. One of the basic rules of
REST is that every „thing‟ becomes data-centric
instead of operation-centric and thus turns into a
resource. This diminishes the footprint of the
application on these resources. Moreover, the internet
is used as an application platform in which all the
resources are accessible through web browsers. This
loose coupling makes it possible to integrate new
devices or „things‟ on a regular basis and makes the
information system light weighted and more simple.
As an example Guinard et al. [8] describe a
composite application in which a sensor node updates
the temperature status of a shipment in an Enterprise
Resource Planning (ERP) system. According to REST
rules, the sensor that measures the temperature is a
resource and will send data only when this is requested
through a web browser. In order to integrate this step
into the enterprise‟s ERP system, SAP MII was used.
This mashup editor allows end users to easily select
resources and create applications for their specific
business needs. By describing this example, the
authors show that by reusing existing web standards
and the REST approach, physical objects can become
part of information networks in a simple way.
Gershenfeld et al. [9] also recognize the need for
limiting the „footprint‟ of an application when it comes
to smart things as resources. They discuss the „less is
more‟ attribute of the Internet of Things and give an
example of a smart medication shelf. Each bottle of
pills contained a tag that channels data to a network
regarding how many pills are still left in the bottle and
whether the owner is on schedule with taking his
medication. Instead of programming a specific tag
reader to acquire data from the bottles, the data is send
to the network first and handled there. This method of
operating requires more bandwidth, but according to
the authors speed should be sacrificed for
interoperability.
Another research in the domain of simplifying the
use of data measured by sensors in „things‟, like
Guinard et al. [8] describe, is that of Le Phuoc [10]. He
proposes a platform, called SensorMasher, to give
2. Related work
In this section previous research on how mashups
can be applied in enterprises is discussed. Additionally,
previous research on business aspects of the Internet of
Things is looked into, in order to bring the two topics
of this paper together.
De Vrieze et al. [2] discuss various criteria for
enterprise mashups. They single out the business
process mashup as being the most valuable for
enterprises. According to this research enterprise
mashups should support the end user in creating and
customizing the application, making it as end user
friendly as possible. Additionally, they describe how
the mashup should be customizable to any other
situation of individual within the same enterprise
information system context. A final characteristic they
discuss is the new insights that mashing up the data
should offer.
De Vrieze et al. [2] also define some key issues in
the area of enterprise mashups. Developing a mashup
is more than just selecting different sources of data. An
important aspect is defining how the data can be used
as a service and in which form (e.g. widget, feed, web
service) it should be offered. Often the individual
services turn out to be too „small‟ to offer significant
value to the entire set of business processes. According
to De Vrieze et al. [2] the services need to be
„elevated‟ in order to be useful for the business process
as a whole.
Hoyer et al. [6] propose a concept in which they
describe how mashups can be used by enterprises. This
concept focuses on commons-based peer production,
and sees users as “knowledge workers who work
primarily with information or develop and use
knowledge in the democratized workspace” [6]. One of
the main characteristics Hoyer et al. [6] describe is that
mashups should be a group effort instead of an
individual achievement, in order to respond efficiently
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
extension of the first paradigm. Decomposition of the
business processes leads to an increase of scalability
and performance and allows better decision making.
The decentralization of the processes gives way to
local decision making, which makes it easier to
implement actuators (smart things that influence the
real world), that can become active participants in the
business process. Even though various benefits are
described, Haller et al. conclude that the industry is
currently still reluctant to widely adopt the Internet of
Things. The main reasons behind this include technical
challenges and the unclearness of real business cases.
(non-technical) users easy access to data obtained by
sensors. Through a graphical interface, users can select
those data sources applicable to their (business) needs.
The interesting aspect of this platform is that it not
only combines sensor data with static data on the web,
but also sensor data amongst each other. Le Phuoc
refers to this specific type of mashup as a Sensor
Mashup. A given example is the combination of sensor
data from a weather station and a traffic camera in a
particular area, and additionally the data from a chest
strap that measures a person‟s heartbeat. Interesting
analyses can be made when combining these three data
sources into one application.
Williams [11] discusses the „real business case‟ of
the Internet of Things, since according to him the
promises that the concept made already ten years ago
did not come true. He debates whether the concept is of
any business value for the current market. One of his
arguments is that the Internet of Things is a concept
invented by academics, while there is no demand from
the market (yet). Additionally, he stresses the
importance that has been put upon the prices of RFID
tags, which were supposed to decrease much more
according to predictions than they did in reality. The
real business case for the Internet of Things according
to Williams lies within the need for specific real time
data in information systems from real time items.
Having said this, he concludes that for some things
there will never be a need to make them smart. For
other things, it will suffice to make them
interrogatable. Out of all objects in our physical world
a pyramid can be created as a structural hierarchy,
which describes the need for objects to be smart and /
or connected to a network. His final remark is that for
the foreseeable future there is no need for most items
to be connected.
Haller et al. [12] also discuss the business value of
the Internet of Things and more in specific for
enterprises. According to this research, the Internet of
Things fits into the future development of a web-based
service economy. Haller et al. describe the „future
internet‟ in which a platform offers the combination
(mashing up) of numerous services and data resources.
The Internet of Things has a role of filling in the gap
between the virtual data and the physical world. Two
major paradigms are described that can establish
economic benefit from the Internet of Things. The first
one is Real World Visibility, and can deliver an
enterprise a competitive advantage by increasing
accuracy and timeliness of information about business
processes. The better these processes are monitored,
the easier it is to improve or reshape them. Fleisch [7]
refers to this as „high-resolution management‟. The
second paradigm described by Haller et al. [12] is
Business Process Decomposition, which is an
3. The Internet of Things-mashup in
enterprises
In this section I discuss the valuable characteristics of
the Internet of Things-mashup for enterprises, as well
as some key issues that enterprises have to deal with,
according to the previously discussed related research.
Keeping these values and issues in mind, I propose a
possible application of an Internet of Things-mashup
for an enterprise in the manufacturing domain.
3.1. Value
The value of the Internet of Things-mashup lies,
according to the discussed related research, in the
following areas:
- Business process management support. Each
business process in an enterprise requires different
information and data. With an Internet of Thingsmashup, specific, accurate and timeliness data
about real live situations and business processes can
be monitored. The value of the mashup in particular
here is the support of the loose coupling of services
in a Service Oriented Architecture. Each
department or function in an enterprise is able to
select those applications required for their business
and mash them back together in a useful IT product.
- Decision making support. Since the Internet of
Things-mashup is easy to adapt or reshape for each
end user in the enterprise, decision making becomes
easier from a low level in the enterprise on.
Decisions can be based on accurate measurements
and observations and will be therefore more
efficient. Additionally, decisions will not
necessarily have to be carried out by human
interaction, since „things‟ are able to communicate
among each other (and in specific to actuators) to
initiate a following step in the business process.
- Easy access to new insights. Since platforms make
it easy for users to query the data that they require,
new insights can be easily offered. When
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
manufacturing plant products are assembled by various
activities, conducted by different employees. In the
plant, the following „things‟ are being measured:
1. Temperature;
2. Air humidity;
3. Intensity of the light;
4. Noise level;
5. Movement of the employees;
6. Identity of specific employee by RFID tag in a
badge that employees carry around;
7. Identity of the product by RFID tag;
8. Number of incorrectly assembled products;
9. Number of correctly assembled products.
Figure 1 shows a schematic overview of the
implementation of the smart things in a manufacturing
plant that could measure the above mentioned data.
The application behind the mashup combines all
these data objects in order to establish in which
conditions the employees work most effective and the
least products are rejected because of incorrect
assembly. Since the products and employees can be
identified individually, it can exactly be seen which
employees contribute to the most correctly assembled
products. The sensors that measure the movements of
these employees can therefore identify the most
effective movements and techniques for a specific part
of the assembly. Employees that outshine in
effectiveness can give training to others, in order to
improve their skills.
Additionally, the influence of temperature, air
humidity, light intensity and noise can be measured on
the number of correctly assembled products. By doing
this, an optimal combination of these factors of the
assembly products can be identified. Once it is clear
which these optimal conditions are, they can be set as a
standard and the „things‟ can act as actuators to self
regulate these conditions.
In order to make this application a true mash up, the
data could be shared among other partner companies.
By combining data online about the work
environments, combinations can be measured and a
predicting algorithm on optimal working conditions
could be established of plants in a certain domain.
Additionally, (supplying) partners could make use of
the data stream in order to verify how much material
should be delivered or what type of material match the
temperature and air conditions best. This could be of
particular importance in processing food.
The above described Internet of Things-mashup
delivers value in all three elements described in section
3.1. It supports the business process since accurate data
about real live „things‟ is added to it. The application
also supports decision making, since information is
given on what conditions lead to the most optimal
outcome. Decisions on the design of the assembly
combining for example sales numbers of an ice
cream stand with measurements of temperature and
location, interesting new insights can be found.
3.2. Key issues
The key issues that can be defined according to the
discussed related research are the following:
- Granularity and relevance. When an Internet of
Things-mashup supports a very local fragment of a
business process, the significance of the
improvement on the total business process might be
questioned. The service that is delivered should
therefore not be too individualistic or detailed.
Additionally, there should be a clear need for the
data that is generated with the Internet of Thingsmashup. In other words, it should be relevant to the
business.
- Design. It is important for an application to have a
usable layout and interface that can be used by any
end user. Since the Internet of Things-mashup
within companies can be created by the end users
themselves, and not by software designers, they
might struggle with the form and shape they should
give to the application to have efficient usability.
- Technology. The technology for the Internet of
Things should be well thought out, since the
„computers‟ placed on the things will be small and
have a small capacity. A „light‟ network that
connects all „things‟ and is easily accessible should
be designed in order to support the use of the data
in a dynamic environment.
Figure 1. Smart things in a manufacturing plant
3.3. Possible application: “Optimal assembly
process identifier and regulator”
In this section I propose a possible Internet of
Things-mashup in the manufacturing domain. In this
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
process are supported. The application also offers new
insights thanks to combination of various data. It can
now become clear for example, that the increase of
incorrectly assembled products in the summer time is
not due to the higher temperatures, but because of the
absence of a certain combination of employees.
The application should also take in mind the three
areas of key issues that are defined in section 3.2. The
granularity of the mashup should be established in such
a way that the improvement is relevant for the overall
business process. Since this is an assembly process,
each fragment of the process is important. Even though
the mashup combines data on a low level in the
process, the influences on the overall process are of
importance and make the application thus relevant.
Since the data is available throughout the entire
enterprise, higher up managers can also consult the
application to acquire their own relevant information.
Buyers in the enterprise can for example measure the
efficiency with the use of certain parts.
The design of the Internet of Things-mashup is in
this case done by the managers of the assembly
process. Their experience in designing these processes
should give them enough knowledge to design an
interface that gives them the data that they require.
Since the data is available throughout the entire
enterprise, higher up managers can also consult the
application to acquire their own relevant information.
Buyers in the enterprise can for example measure the
efficiency with the use of certain parts.
The technology used in this application, consists
mostly of „regular‟ hardware (e.g. thermometers, RFID
tags, decibel meter, cameras). In order to keep the
network „light‟, the data should be sent to a server first
before it is analyzed or edited. By doing this, the
„things‟ do not need much capacity to function. For
example, the images that the cameras make of
employees can be analyzed into patterns with
specialized software after the images have been
captured. The camera only sends out raw data.
have to do with granularity and relevance, design and
technology.
After answering the research question I have
proposed an Internet of Things-mashup for a
manufacturing plant, called “Optimal assembly process
identifier and regulator”. With this example I have
illustrated the three main areas in which value can be
created for an enterprise with an Internet of Thingsmashup and how the key issues can be overcome.
It has to be noted, that due to lack of time and
space, the literature research in this paper is quite
limited. Therefore, future research can be conducted
more elaborately in both the domains of this paper in
order to establish a framework which „guides‟
enterprises to the creation of valuable Internet of
Things-mashups conform to their business needs.
5. References
[1] D. Benslimane, S. Dustdar, and A. Sheth, “Services
mashups: The new generation of web applications,” IEEE
Internet Computing, vol. 12, no. 5, 2008, pp. 13-15
[2] P. de Vrieze, L. Xu, A. Bouguettaya, J. Yang, and J.
Chen, “Process-oriented Enterprise Mashups,” 2009
Workshops at the Grid and Pervasive Computing
Conference, 2009, pp.74 – 71
[3] T. Hermanns, D. Mirandolle, “Improving communication
in real estate project initiation: an explorative case study
using a mashup”, Proceeding of the 20th Annual Conference
of the International Information Management Association,
Utrecht, 2010
[4] A. Jhingran, Enterprise Information Mashups,
Proceedings of the 32nd international conference on Very
large data bases, VLDB, 2006, pp. 3-4
[5] B. Büchel, T. Janner, C. Schroth, and V. Hoyer,
Enterprise Mashup vs. Service Composition: What fits to
reach the next stage in End-User Development?,
Wissensmanagement, vol. 145 of LNI, 2009, pp. 260-269
4. Conclusion
[6] Hoyer, V., & Stanoevska-Slabeva, K. Design Principles
of Enterprise Mashups. Wissensmanagement, 2009, 242-253
In this paper I have reviewed literature in the
domains of enterprise mashups and the Internet of
Things, in order to find out what the value is of the
“Internet of Things-mashup” for enterprises. By
exploring related research in both domains I have
found three areas in which an Internet of Thingsmashup can add value to an enterprise. These are:
business process management support, decision
making support and easy access to new insights.
Additionally, I have found three key issues of applying
such a mashup in an enterprise domain. These issues
[7] E. Fleisch, “What is the internet of things?: an economic
perspective”, ITEM-HSG, Auto-ID Lab St. Gallen, 2010
[8] D. Guinard, V. Trifa, T. Pham, O. Liechti, Towards
Physical Mashups in the Web of Things, Sixth International
Conference on Networked Sensing Systems (INSS),
Pittsburgh PA, 2009, pp. 1-4
[9] N. Gershenfeld, R. Krikorian, D. Cohen, The Internet of
Things, Scientific American, vol. 291, 2004, pp. 76 - 81
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
[10] D. Le Phuoc, SensorMasher: publishing and building
mashup of sensor data, Digital Enterprise Research Insitute,
National University of Ireland, 2009, pp. 1-5
[12] S. Haller, S. Karnouskos, C. Schroth, The Internet of
Things in an Enterprise Context, Lecture Notes in Computer
Science, vol. 5468, 2009, pp. 14-28
[11] B. Williams, What is the real business case for the
internet of things?, Synthesis Journal, ITSC, 2008, pp. 127135
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Smart Cities and Internet of Things
Oliver Haubensak
ETH-MTEC
[email protected]
April 14th, 2011
projects being in their starting phase. Masdar City and
PlanIT Valley will once built, produce more renewable
energy than they consume, as well as recycle most of
the water used. Furthermore, I am presenting an
already installed smart solution: monitoring the traffic
in Zaragoza, Spain.
Abstract
Smart city is still a fuzzy concept and being broadly
used. In this paper I am going to elaborate
opportunities and challenges as well as explain the
reason why there is an urge for smart cities. Smart city
concepts will be presented, among them Masdar City,
a city entirely built in the desert, which will once be
home for 50’000 inhabitants and claims to produce
entirely renewable energy for the whole consumption
need as well as recycle 80% of the used water.
2. Opportunities and Challenges
Quickly we can see that there is an opportunity of many
applications in the field of the internet of things in any
of the mentioned fields. “The internet is extending its
reach to the real world trough innovations” [3]. Where
opportunities exist we can also expect challenges [4].
In order to have increased returns and a successful
system, we require an important number of devices /
users and interactions. Devices and platforms need to
be somehow heterogeneous to reach interoperability. A
coming challenge will be the mining and processing of
the data as well as providing secure access and
continuously control privacy. Unified enriched and
interoperable data description models need to be
provided. A further challenge will be mobility. Ad-hoc
access and service continuity will be important.
1. Introduction
Smart City is a term used in many publications and
articles. It seems that this label is somehow still a fuzzy
and inconsistent concept and needs to be clarified for
this paper. The concept discussed in “Smart cities Ranking of European medium-sized cities” [2] seems
appropriate for the first attempt. Smart cities can be slit
up in six dimensions: Smart economy, smart people,
smart governance, smart mobility, smart environment
and smart living. These dimensions are based on
competitiveness,
social
and
human
capital,
participation, transport and ICT, natural resources and
quality of life. This definition was used in order to rank
cities in their “smartness”. For example, innovative
spirit is part of the Smart Economy dimension, which is
in turn measured by patent applications per inhabitant.
After looking a little bit further, this definition could be
found: A city can be called smart,” when investments
in human and social capital and traditional (transport)
and modern (ICT) communication infrastructure fuel
sustainable economic growth and a high quality of life,
with a wise management of natural resources, through
participatory governance”[17]. This definition defines
exactly the projects I am going to present in this paper.
In the next sections, I will introduce the reader to
opportunities and challenges, why we need smart cities
and the path towards them. Finally I will present
Masdar City, PlanIT Valley and Smart Santander. All
3. Smart Cities – But why?
The question arises - why do we need smart cities? The
answer is closely connected with our today‟s society. In
many countries we can see the development that
younger people move for education or better work
prospects to urban areas and most of them are not
willing to give up these advantages. The result is that
already today almost 60% of the world‟s population
lives in urban areas [1]. Cities account for 75% of
greenhouse emissions, while only occupying 2% of
worlds surface [6]. It is expected that the amount of
people living in urban areas will double until 2050 and
by 2015 1.2 billion cars will be on the road – making 1
car per 6 people [6]. Another factor is demographics.
The population is aging and living longer due to
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
they can alter collectively to get a more efficient and
flexible system [5].
advance in medicine and many other areas. This factor
is letting the population further grow and the need of
more space becomes obvious. Cities become
increasingly more competitive. Success criteria‟s are
attracting business, creating jobs, offer a rich culture
and attract tourism. All this also brings draw-backs, as
citizens become more demanding trough this
competition. The most obvious problems arise out of
the main infrastructures such as electricity networks,
transport networks and waste management. These
infrastructures need to be well planned ahead in order
not to collapse within time. Resources are getting
scarcer in the coming years, looking for alternative and
sustainable use becomes a core importance. This
brings us to the last and maybe the most important
drivers for Smart Cities: Climate Change. As we all
know, our live is locked-in to carbon technologies. We
ship fruits around the world, use cars, take planes,
outsource whole productions to Asia and produce
electricity with coal. Green house targets have been set,
but it seems that reaching these goals will be a big
challenge in the coming years. We are locked-in to a
huge system between industries, government and
society. Many Smart cities try to elaborate new systems
and technologies for a sustainable development.
Many Information and Communications Technologies
(ICT) improved services on department levels such as
mobility, eGovernment and such. These technologies
make services more efficient and lead to a better
informed citizen. Many cities try now to push this
concept of smart cities further and search for solutions
over the limits of the departmental level to a city wide
approach. Such approaches will create economies of
scale and scope. This resulting in running the city more
efficiently, providing a more interesting place to work
and live, encouraging resource efficiency towards
climate change mitigation and creation of jobs [5].
Key of many applications will be measuring and
sensing. Systems will adapt and learn from
infrastructures and activities reporting their state and
behavior [5]. A famous quote1 says that „if you can‟t
measure it, you can‟t manage it” and can be applied in
this framework. Managing of for example
infrastructures can reach new levels through gathering
data and constant learning from millions of nodes
reporting their state and/or behavior in real-time. A set
of development areas is presented in the table shown
below.
30% of carbon emissions could be reduced in London
just trough behavior change and a project in Helsinki
states that even 50% of a citizens carbon emission are
due to their lifestyle choices [5]. Two main drivers for
behavioral change are social proof and active learning
[5]. Trough new development like social media this
becomes available. Smart Metering is a broadly
discussed topic within the internet of things and many
new developments are already on the market. Those
devices are measuring the consumption and through the
real time feedback, stimulating its user to adapt his
behavior. This might be with comparing to himself or
over social platforms and interfaces with the rest of the
world. This confirming the statement of the two main
drivers for behavioral change.
City System
Example Smart Solution
Transportation
Public transport monitoring
Traffic monitoring and routing
Municipal fleet management
Parking information
Electronic Records Management
Remote Monitoring Systems
Hospital Asset Management
eLearning
Connected Campuses
Video Surveillance: video analytics/workflow
Enhanced Emergency Systems
Smart-Meters
Monitoring heating, lighting, security systems,
water management, structure
Electronic sensors to detect toxicity in landfills
Waste-tracking
Improve the efficiency of waste collection
Facilitate automation of city processes
eGovernment
Healthcare
Education
4. The path to a smart city
Public Safety
and Security
Building
Management
Today most of us carry a smartphone. These phones are
equipped with internet connection, positioning systems,
accelerometers and some with RFID readers. With the
already today existing well developed fast broadband
network in urban areas, we have the already important
necessary tools towards a smart city. It is fundamental
that cities need to provide the architecture for future
innovations, so that companies can innovate. Also
citizens need to realize the real value of future
innovations and contribute their part. Smart cities help
to make urban systems clear, simple and responsive
trough modern technology. The citizen shouldn‟t see
the city anymore as rigid and inflexible, but should
start and be engaged to interact - finally to realize that
Waste
Management
City
Administration
Development Areas, adapted from Forrester [18]
In some papers we can already find the term City 2.0
which consists of the vision of a city where the urban
environment‟s constantly changing dynamics can be
monitored [7]. This includes but is not restricted to
1
34
Source is controversial discussed
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Masdar City, an entire new city for 50‟000 inhabitants
which should run carbon-free as well as the
SmartSantander project, PlanIT Valley and two
concrete applications.
snow/rainfall, traffic, movement of citizens and usage
of resources (electricity, water, gas and sewage
systems). The idea behind is to be able to act before
problems arise. Changing the traffic pattern
dynamically might be one of these advantages.
5.1. Masdar City
Monitoring the streets of a city and measuring
environmental figures is already reality in many cites.
Already in 1995, Redwood City in California started to
deploy acoustic sensors in their streets, able to detect
gun shots. The police are then able to respond without
an emergency call and know immediately where to go.
This system is now deployed in more than 30 U.S.
cities [7]. Many cities also have a vast network of
video surveillance of streets on public infrastructures
such as public transport. Also cities start to install
sensors, measuring environmental factors, like
emissions. Private companies gather data from citizens
- let us just think at mobile phone operators. All those
already existing sensors and its data together mashedup give us already huge opportunities. Let us assume
that almost every citizen is in the possession of a
mobile phone. Movements of citizens walking, in
public transport or in private cars could be tracked and
patterns analyzed. This could be used for planning and
future decisions for example adaptions of public
transport. Also traffic jams could be spotted
immediately, citizens informed and traffic rerouted.
All this are excellent ideas, but in reality a real
challenge to realize. First there are the privacy
concerns of users which need to be considered. A
citizen probably doesn‟t mind pollutions sensors, but
might be more sensible to cameras and sensors which
detect their motion or follow their use of resources.
Also barriers can be seen in the law of each country
and how the government and the industry have to
handle the data regarding privacy concerns. We have
seen in many countries that cities departments working
poorly together and such ideas in general need a
rethinking of the rigid patterns existing within cities
administrations.
Masdar City [8] is planned in the desert outside of Abu
Dhabi, covering 6 square kilometers and will be home
to 50‟000 inhabitants, up to 1‟500 businesses and a
new university. The aim of the Masdar City is clear:
Fossil fuel free zone, 100% renewable energies and
zero waste. 80% of the used water will be recycled
onsite.
Proposed Masterplan of Masdar City [8]
Private vehicles will be prohibited in the city. Modes of
transport will be, electric vehicles, cycling, a so called
Personal Rapid Transit (PRT) system and a Light Rail
System (LRT). The transport concept is as such that
there is a maximum distance of 200 meters to the next
station. An artificial basement will be created so that
the pedestrian level will be raised to accommodate the
various systems and transport infrastructure. In the final
stage there should be 3‟000 PRT vehicles ( for 4 adults
+ 2 children each) installed serving over 85 stations
and making 130‟000 trips a day. The longest journey
should take no longer than 10 minutes. A PRT vehicle
can run up to 60km on a 1.5 hour charge with its
Lithium-Phosphate batteries. On the same basis a
Rapid Transit System (RTS) will be deployed, able to
transport 2 pallets up to 1‟600kg per trip [9]. Although
it seems that the PRT System has been partly
In the field of smart cities there is a lot of development
and research going on at the moment. In the next
section I will introduce you to some of the most
important projects at the moment.
5. Current Projects
As already stated earlier in this paper is that the term
“smart city” is used broadly. There are plans for entire
cities, business parks as well as many single projects
which can contribute to the efficiency of a resource. In
this section I like to introduce the master plan of
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
abandoned at this time and buses or trams might be
implemented in the plan as well.
The first phase was planned to be finished by 2009, but
now rescheduled to 2015 due to the financial crisis and
missing funds. Finalization of the whole project should
be 2025 [10]. At the time of writing, the first buildings
are finished and the Masdar Institute is running since
last year. There is also a small network of PRT already
running.
In terms of Internet of Things not much is outlined
within this project, but a lot is imaginable. Most can be
found in a promotional video: «During the planning
and design of Masdar City, the engineers identified
more than 25 software applications that would be
required to create and maintain a sustainable city.
These applications tie into and control the smart grid,
smart appliances, smart buildings, transportation
systems and the city wide public information systems.
Many of these systems relay real-time sustainability
and energy consumption information to the engineers
of Masdar City. » [11] Further research gives us some
clearer and more profound insight into those plans.
Masdar City will test the new smart appliances from
General Electric (GE) for example. These appliances
include refrigerators, stoves and washer/dryer machines
which will be equipped with smart meters and
connected to the cities smart grid. This will allow
transmitting real-time consumption data and allows that
non-essential functions can be run during off-peak
usage hours [12].
Planned architecture of SmartSantander [13]
A big difference to common research facilities is that
this project will be deployed in the real world and not
just within the walls of a laboratory. Parking
monitoring has been chosen to be the first application
within this framework. Parking is a big issue in almost
every city. The application will not only focus on
parking availability, but also on a wider approach like
traffic situation and environmental issues [14]. Other
coming projects might include environmental
monitoring where users can see a dynamic map of the
environment (actual pollution), Control of buses and
taxis stops and monitoring of public bicycles and
Urban waste management. Those projects will face a
couple of common challenges as all these sensors need
to be theft- and weatherproof, need to be connected and
probably the biggest issue that they need power [14].
Almost none of the subprojects is known yet as the
program just started. During this 36 month program,
SmartSantander will provide two Open Calls where
external users can run experiments using this
framework and also be funded.
5.2. Smart Santander
Maybe one of the most important projects in respect of
Internet of Things and Smart Cities is the
SmartSantander Project in Spain. The city in the north
of Spain counts 180‟000 inhabitants. This year already
8000 sensor should be installed and up to 20‟000 for
completion of the project. This project is supported by
many important companies and universities as well as
supported by the EU with 8.7M Euros [14]. The aim is
to create the world‟s first and unique experimental
research facility for applications in the field of Internet
of Things. Key functions will be to validate approaches
to the model of Internet of Things. Evaluating
management protocols and mechanisms, device
technologies, security and identity management will be
of high importance. Finally also the assessing of social
acceptance of Internet of Things Services and
Technologies within a real population will be the aim
of this project [13].
5.3. PlanIT Valley
In parallel of Masdar City there are similar plans in
Portugal. In the next years, they will build a city, called
PlanIT Valley [15], on 1700 hectares of land outside of
Porto. The aims are high as for Madar City: the city
should produce 150% of energy needed, reducing
waste and recycle most of the water. In this project,
financing will come entirely from private equity. This
is particularly interesting as companies can become
partners when paying a yearly membership fee. This
entitles them to be part of the PlanIT Network and help
to develop the city. The planners see this city as an
open test bed where companies can develop new
services. Some new developments will be successful,
some won‟t.
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
existing electricity grid. Without a robust
infrastructure, this concept won‟t work. Basically the
problems in a grid are the different consumption and
production patterns during the day and seasons.
Consumption has their peaks at midday and evenings.
Depending on the type of power production, for
example solar or wind power can be pretty inconstant.
This can be solved through an intelligent system, where
appliances can send and receive data. We discussed
those examples for Masdar City and their cooperation
with GE and their new appliances.
Before the idea of this project was born, one of the
initiators saw the problem of purchasing in the building
construction. Every company has their own supplychain and too much waste accrues. For example it took
5 years to build an airplane factory and assembly line
and for the more complex airplane it just takes 3 month
to fully assemble it. Those learning‟s from other
industries should now be applied on the traditional
construction industry which is becoming outdated with
the new techniques, designs and processes. Through
these improvements, the initiators hope to save up to
40% of building cost and hope to construct buildings
up to 50% faster. It is obvious that Internet of Things
will help these processes for example trough supplymanagement, for example RFID tagging.
PlanIT have important partners such as Microsoft,
Cisco, Massachusetts Institute of Technology and
McLaren Electronic Systems onboard. The idea is to
implement an Urban Operating System (UOS), a
common platform for enabling a smart city to evolve in
each aspect. The system will be fed by a vast sensor
network spread out over the whole city and in every
function of the urban environment. Data will be
collected, combined and analyzed in order to derive
better knowledge over different parts of the
urbanization. Data is planned to be stored indefinitely.
This helps the city to continuously optimize its system
and to predict possible outcomes. The system will be
able to react real-time, for example avoid outages of
electricity or water before it even happens, or traffic
control. In case of an accident, the system can predict
impacts of the coming hours by merging different data
such as time, season or weather. Traffic will be
rerouted and means of public transportation made
available. New features and applications can be added
at a later point of time to the UOS. This is leading to
new developments and business plans for the partners
of the PlanIT project.
On the base of this plan, a reliable and vast sensor
network is needed. Those nodes need to sense physical
states, properties and/or events in the environment and
finally send the acquired data to the UOS. Data also
needs to be received by the nodes (houses, traffic
control, heating, lighting…).
Lightning control should be highly intelligent. The
system will analyze the user in such an extent that it
will recognize its patterns and merge it with the
knowledge of weather and sunlight status. Finally the
system will be able to overtake and knows the needs of
its user, even the preferences when cooking or
watching television.
Whatever smart city project we are looking at, smart
grid is playing an important role. It sounds like it is
something new, but it‟s just an enhancement of the
5.4. Smart Applications
As you probably recognized, there is not much
information of complete projects. Before coming to the
conclusion of this paper, I like to introduce the reader
to two running concepts in the field of sensing which
we can well imagine becoming part in the already
mentioned smart city projects.
Android-Application showing Zaragoza’s real-time
traffic [16]
One of them is the traffic monitoring system in
Zaragoza, Spain [16]. 150 sensors set up all over the
city can monitor up to 90% of the urban routes. The
data is collected by sensors which are able to detect
mobile devices (Bluetooth, WIFI frequencies). The
data is then forwarded to a server for processing. The
traffic patterns will be displayed at the traffic control
center. Also displays within the city are used to display
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
average travel times and warnings. Citizens can access
the real-time status of the roads by internet over their
smartphones or at home.
6. Conclusions
As defined in the introduction, we can think about
many new applications to come in every of the six
dimensions of a smart city. Mostly concepts focus on
scarce resources, but we shouldn‟t just restrict us to
that field. There are many applications making daily
life more interesting and opens new fields of
businesses.
You probably already found out, that within these
master plans of smart cities, there isn‟t much
information on Internet of Things developments. We
can just imagine how it might look like.
Architecture of Zaragozas Traffic System [16]
The data serves the city to manage better their traffic
wardens and to learn the dynamics of their city. Further
they will help the government to implement new
adequate policies.
Another important discussion is sensors build into the
infrastructure, mainly buildings. Already since some
years, larger bridges are equipped with sensors and are
monitored for oscillations. The Fraunhofer institute and
MPA Braunschweig in Germany developed a new
sensor, able to sense rusting parts and cavities in bridge
structures. Mainly in the northern hemisphere, salt is
used to defrost roads in the winter. This salt can reach
important metal structures in bridges and create
cavities. Also bridges close to the sea are affected by
the harsh environment. In the worst case bridges can
collapse due to these impacts.
There will be many obstacles to overcome. Does the
citizen actually need to give up a part of his privacy?
Does he want that the city knows when he left home or
boarded a bus? Privacy concern will play an important
role in this field, so that a smart city doesn‟t converge
to a censored and over controlled area.
The developers and initiators of such projects need to
think a little bit further than just the building and
initiation phases. What will be years after the
completion of the project? The wireless networks and
its application need to be open-source and compatible
with new applications, so developers can continuously
improve the network and its appliances. There is a need
of common language, i.e. protocols. Let us just think at
all the different companies developing smart appliances
for the smart grid. To keep such a network open for
new innovations, keep it stable and reliable and finally
consider privacy will be a major challenge.
New Sensor, able to detect rust in bridges – developed
by the Fraunhofer Institute and MPA Braunschweig
[16]
This sensor isn‟t equipped with a power source. In
order to read the data, power is applied trough
induction and the data acquired. With this data, the
structure of the bridge can be monitored constantly and
maintenance coordinated accordingly. At the time the
institute is testing the system on a test bridge.
Those are just two “little” applications how we can
make a city smarter and we can imagine that there are
endless of ideas possible to develop and implement in
the future.
38
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
20-000-sensoren-ueberwachen-spanische-stadtsantander.html
Retrieved 23-03-2011
[15] “Living PlanIT”, Living PlanIT SA, Retrieved 0404-2011, http://living-planit.com
[16] “Bitcarrier, Wireless real-time traffic solutions”,
Bitcarrier S.L., Retrieved 04-04-2011,
http://www.bitcarrier.com
[17] Caragliu, A., Del Bo, C., Nijkamp, P.: Smart
cities in Europe. Series Research Memoranda
0048. VU University Amsterdam, Faculty of
Economics, Business Administration and
Econometrics (2009)
[18] “What's new in Smart Cities”, Bélissent Jennifer,
Forrester Research, Retrieved 11-05-2011,
http://www.amr.ru/upload/iblock/392/Smartcities.pdf
7. References
[1] “People Statistics: Percentage living in urban areas
by country”, Rapid Interlligence, Retrieved 22-032011,http://www.nationmaster.com/graph/peo_per_liv_
in_urb_are-people-percentage-living-urban-areas
[2] Giffliger et al. 2007. Smart cities - Ranking of
European medium-sized cities. Final Report
[3] “Real World Internet - Position Paper”, European
Future Internet Portal, Retrieved 22-03-2011,
http://www.futureinternet.eu/fileadmin/documents/madrid_documents/ses
sions/Real_World_Internet_Position_Paper_vFINAL.p
df
[4] “Real World Internet, Smart City and Linked Data”,
Presser et al., 2010, Retrieved 22-03-2011,
http://linkeddata.futureinternet.eu/images/b/bf/Presser_Linked_Data.pdf
[5] “Smart Cities - Transforming the 21st century city
via the creative use of technology”, ARUP Corp.,
2010, Retrieved 22-03-2011,
http://www.arup.com/~/media/Files/PDF/Publications/
Research_and_whitepapers/ARUP_Smart_City.ashx
[6] “SmartSantander - a Smart City example“, Krco
Srdan, Ericsson, 2010, Retrieved 23-03-2011,
http://www.smartsantander.eu/downloads/Presentations
/smartsantander1.pdf
[7] “Sensors Make Cities Smarter”, Patton Zach, 2010,
Retrieved 23-03-2011,
http://www.majorcities.eu/pics/download/1_127839842
3/Governing___Sensors_make_cities_smarter.pdf
[8] “Masdar City”, Retrieved 23-03-2011,
http://www.masdarcity.ae
[9] “Masdar PRT Application”, 2getthere B.V.,
Retrieved 23-03-2011,
http://www.2getthere.eu/?page_id=10
[10] “Öko-Stadt Masdar City vorerst gestoppt “, Hahn
Melanie, Daily Green, Retrieved 23-03-2011,
http://www.dailygreen.de/2010/03/12/oko-stadtmasdar-city-vorerst-gestoppt-4032.html
[11] “Masdar City Design” (Video), Retrieved 23-032011, http://en.com/Masdar_City_City_Design#
[12] “Masdar City to test GE 'smart' appliances“,
Lombardi Candace, cnet news, 2009, Retrieved 23-032011, http://news.cnet.com/8301-11128_3-1036727954.html
[13] “Smart Santander – Future Internet Research &
Experimentation”, Retrieved 23-03-2011,
http://www.smartsantander.eu/
[14] “Projekt Smart City: 20.000 Sensoren
überwachen spanische Stadt Santander”, Hemmerich
Lisa, 2010, Retrieved 23-03-2011,
http://www.netzwelt.de/news/83222-projekt-smart-city-
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
Hability
An integrated smart meter framework for home and mobility use
Daniel Mauch, D-MTEC
[email protected]
June 15th 2011
depleted in the near future, energy usage has not
declined. In spite of the awareness of public
consciousness and unaffected by technological progress
in energy efficiency a change in this trend has not been
noticed. Increasingly numbers of small devices add to
the overall rising electricity consumption in private
households and sum up to an overproprotional increase
over the last decades. Electricity remains percepted as
relatively cheap, abundant, and unaffected by
consequences.
0
Abstract
Transportation and electricity use in households are
responsible for half of the energy use of our society.
Despite the common knowledge on environmental
implications of habits, little economic nor social
incentives exist to change acquired behaviour
patterns. Automated data collection, processing and
exhibitation of decision relevant information can close
this perceptional gap. Intelligent devices become
ubiquitous through institutional functions of
innovation systems: Smart meters are being deployed
at home and high-performance phones – equipped
with a variety of measuring elements – are gaining
market share. Alignment of various sensors at home
and abroad, data logging on a small server,
information processing and instantaneous and
attractive display can lead to learning effects leading
to change of usage habits. In this paper I will try to
give an introduction to drivers of behavioural decision
making, a market overview of existing smart meter
technologies and applications and develop an example
for an integrated approach.
Transportation occupies the largest share on primary
power and thus conceals the highest challenge and also
chance to contribute to sustainable energy usage. In the
motorized transportation sector we can distinguish
between private individual, private public and
individual human powered mobility. Efficiency has
become an increasing factor in motorized mobility,
consumption figures a selling argument – even a
legally prerequisited label. And cars are getting more
efficient, unfortunately this progress is thwarted by
additional weight of built-in convenience and comfort
solutions.
1
Introduction
Reduction in energy usage is one of the human society
biggest challenge towards an equilibre and sustainable
development. In 2008, total world energy consumption
was 474 exajoules. This is equivalent to an average
annual power usage rate of 15 terawatts (1.504·10 13 W)
[1]. While the total energy consumption decreased in
2009 for the first time in 30 years (as a result of the
economic crisis) [2], the share of the private household
part is constantly increasing [3]. In Switzerland the
total energy consumption in 2009 is about 900'000
terajoules, with mobility and households occupying the
largest shares (35%, 29% respectively) [4]. Electric
appliances are responsible for 60% of the electricity
use in Switzerland [7].
The societal challenge of energy consumption reflected
in institutions such as government, media, public
cognition, technology and functions like information
and incentives to energy efficiency has nevertheless not
yet found translation into behavioural transitition. But
why?
3
The behavioural gap
Predominant explanations of drivers of decision
patterns can be found in behavioural economics and
environmental psychology.
The approach of environmental economics extends
economics with insights of the fields of psychology to
give an integrated answer to phenomena and selective
choice observed in reality contradicting classical
market mechanisms. Thus not only price but also
social, cognitive and regulative factors are used to
explain the variety of different products, solutions and
the respective choice.
2
Institutional Arrangement
At the end of 2006 the EU pledged to cut its annual
consumption of primary energy by 20% until 2020 [5]
and subsequently has adopted this policy by passing a
Directive (2006/32/EC) named “Energy end-use
efficiency and energy services” demanding “individual
metering and informative billing that shows [..] actual
energy consumption”[6].
Theories in environmental psychology build upon two
most commonly used models, the rational choice and
norm-activation
to
support
pro-environmental
behaviour [36]. The first, rational choice models,
explain decision making by maximizing marginal
utility in terms of cost and benefit. Knowledge in
Despite the fact, that consumption has increased and
given the natural resources of non-renewable energy is
40
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
correlation of cause – effect tuples leads to concern
about environmental issues which in turn is followed
by energy-conserving behaviour. The latter, normactivation models, derive behaviour by collective or
personal morale. Awareness of consequences of
personal actions to the collective guides decision
making towards pro-environmental behaviour, which
in extreme even might supersede subjective, rational
utility.
The process of electricity consumption is in most cases
a mute, silent event. If one could hear energy usage
distinctively – as eg. when vacuum-cleaning the floor
or hair drying – perception would be different and
other usage patterns emerge. A feedback loop is clearly
missing in this context.
3.2 Transportational energy usage awareness
The energy consumption of the mobility sector with a
share of one third of primary energy is by the means of
automated usage information processing barely tapped.
Automotive development has a longstanding tradition
with highly spezialized fields, in fuel efficiency as well
as in consumer electronics. Convergence of car
computing and personal devices has nevertheless not
been considerably and commonly supported.
Based on these theories we can derive that decision
making is primarily driven by insights, facts. We
commonly are unable to derive implications of our
actions, because energy consumption is usually a mute
process. Informational feedback is the key behavioural
driver next to personal know-how or to a collective
normative. Elucidation in environmental terms has
arrived in the institutional structures, but the gain to
pro-environmental behaviour is marginal in the case of
presenting the the information only. Not only the
content, but even more the the context: specificy,
timing and placement als well as the design are
critical to the effectiveness of the message [23].
Governmental strategies to reduce energy efficiency, as
eg. Energie2000 in Switzerland with its fuel saving
programs [27] was a great success and raised public
awareness, but remains unpursued in its extent and is
thus not sustainable over the long term.
4
Personal Feedback systems
On May 19th 2011 Toshiba has announced to buy Swiss
Landys+Gyr, which has a longstanding tradition of
meter fabrication and were recently chosen to supply
the worlds largest Smart Grid in China with intelligent
power meters [34]. With Google Power Meter [32] and
Microsoft Hohm [33] two other major technology
players have started their program of commercial
smart sensor systems.
4.1 Measuring home electricity
Within the last years a vast variety of home electricity
displays have entered the market. On a technological
basis we can separate single-sensored from multisensored or per-device systems. The former approach
places the sensor on the main incoming feed (usually
the fuse box or the meter itself). The latter solution
uses smart power outlets or intelligent chips for each
connected device. The communication to a central
server can either be through the powerline itself, a
dedicated separate wiring or wireless protocols
(Bluetooth, WiFi, Zigbee).
Figure 1. Examples of eco-feedback displays on smartphones
(left: Google Power Meter [38], right: eMeter interface of Bits to Energy
Lab project, ETH Zürich [37])
3.1 Electricity consumption is unperceivable
Through political regulations like eg. labelling of
consumer appliances as well as significant increase in
the efficiency of household appliances (refridgerator,
oven, standby drawing) the electricity usage of
households should be expected to decline, but instead
rised over the last years, thus is increasingly dependent
on consumer behaviour. Similar households can vary
up to 2.6 times from the least to the most energy using
in terms of energy consumption [29]. But even people
willing to change their behaviour and save energy
cannot get access to detailed usage information, it's
simply not available or easily accessible.
Commercial products with a single, central sensor have
been made available eg. by Wattson [17], Wattcher
[18] or Onzo [19]. A single, central sensor offers lower
costs and easier integration into existing installations.
Considerable research in this field has been conducted
lately by M. Weiss [24,25,26]. Power consumers in this
operating scheme are recognized using load patterns
and operationalized through an user interface on an
iPhone.
As a personal example from my own experience: I do
receive a bill from my electrical power provider in my
mailbox regularly. But four times a year its only a
quarterly “on account” bill with an extrapolated
number, and once a year a settlement containing a
number representing my consumption compared to the
previous period. On this information base it is
impossible to derive a decision driven learning.
Another inititative aims towards a standardization of a
per device powerline chip [28]. This multi-sensor setup
allows for each device to identify itself autonomously
to the server and bilateral communication. The
drawbacks are on the cost side. First commercial
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Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
The approach of determining the usage of public or
individual transports by tracking Global Positioning
System (GPS) data and activity inference has been
already conducted by applications like UbiGreen [13],
or ecorio [14].
The possibility to infer from movement patterns to
transportation means is appealing, as it doesn't require
any user interaction – as long as it has learned
individual characteristics of a persons preferences and
possibilities. It is technically viable to refine accuracy
by combining GPS with accelerometer and map data.
Figure 2. Electric power home sensing system setup model with
different configuration options (from left to right, top row to bottom): A
local display, local database, central server with sensor, power
consumers; mobile display, remote database, local server, distributed
sensors and electricity consumers. Various combinations of
hardwiring/wireless, single-sensor/central-sensor, local/remote database
and displaying device are possible.
5
Hability
We have seen that several solutions for measuring,
storing and displaying electric home power usage exist.
It is now up to the market to emerge a standard. The
institutions have been set up and smart meters are
started being deployed widely. In the following I want
to present a convergency approach for a device which
covers feedback for home electricity use and energy use
on transportation.
available components and solutions were available by
the end of last month [30, 31]. This solution directs
more towards home automation.
4.2 Measuring transportation energy consumption
Several approaches exist to collect transportation data
and energy consumption. I will briefly introduce some
examples and applications.
Modern vehicles nowadays measure the fuel use on a
short and long term basis accurately and might even
communicate the consumption via the on-board
display. Ususally this information is displayed
instantaneous on the basis of current and average
usage. Interfaces for further processing exist through
the on-board diagnostics bus (OBD-II) [8] and its
interface, which is mandatory for every new car sold
since 1996. There are applications on the market,
which simply write all available data to a memory chip
[9], or transmit wireless to a smartphone
[10,11,12,21]. But all these solutions need a connector
hardware, plugged to the OBD-II outlet, which at least
is usually conviently located in the passengers cabinet,
but it is an additional investment and a barrier to
usage.
Figure 3. Definition of “hability” according to Merriam-Webster [35].
Our setup exists of a home appliance, preferably a
single sensor central server solution, and a smart
phone. Electricity usage is continously measured,
stored and displayed on demand on the handset. This
scheme has been already developed and can be
deployed immediately.
But what about mobility? Detailled information about
private transportation would technically available, it's
just a question of motivation, convenience and cost to
set up car-data tracking and a respective feedback
system.
With the approach of GPS-tracking of the movement
the transportation mean can be determined by pattern
recognition, and tracked on maps with high resolution
in an automated way. In the case of private motorized
transportation theres just one little crucial piece of
information missing: the amount of fuel consumption.
Common solution are based on assumptions or generic
car types and thus provide only estimated numbers. As
the process of refilling the gas tank is a discrete task
and has to be proceeded manually, we have a
discontinuum in the process. Now if we have this
interruption, how can we provide the information to
flow? Of course all gas stations or meters could be
equipped with wireless emitters or NFC chips,
transmitting the amount and the cost of the purchase to
the customers smart device, but besides economic and
security drawbacks of setting up this kind of
infrastructure, there would still be the need of manual
An alternative to measure the fuel consumption would
be the use of the internal accelerometer on a mobile
device [15]. With this solution it is still necessary to
adapt the application to the individual efficiency of the
transport means – be it private or public – and calibrate
the readings.
For manual recording of fuel data there are already
several applications [20,22]. Because they rely on
accurate off-line transcription of mileage and energy
consumption and are solely manual feed, they aren't
further discussed within this context.
The energy usage of people using public transport can
only be estimated. Even though trains, trams and some
busses are electrical driven, no information on a per
user or per ride level is publicly available.
42
Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.)
interaction for the selection of the right meter – device
pair.
6
Conclusions
Smart electricity meters are or being installed in
households in large numbers in the US by now and in
the EU in the coming years because of governmental
requirements aiming to reduce power usage by
providing detailled information.
With the technology of Optical character recognition
(OCR), which is able to extract processable data from
images, we have the possibility to offer a more
convenient way and lower the entry barrier of the
manual interaction at the gas station: just take a picture
of the meter at the station after the refill:
Information on energy use of individual mobility can
be revealed through the use of integrated sensors be it
in cars or indirectly via hand held devices. To refine
accuracy of motorized mobility energy usage, a semiautomated fuel usage data capturing application is
developped. This lowers the barrier of collaboration,
eases information flow and allows real efficiency to be
computed. Our personal computerized daily companion
– the smart phone – is the perfect platform for a
interactive feedback system. Combined with added
services for personal fun and challenge we create an
ecological worthwile application.
Figure 4. Gas meter showing figures for cost, amount and prices after a
refill. These numbers, once electronically interpreted, are fed into
automated processing application.
It remains to further investigate whether an in situ
processing of imagery by an OCR algorithm is
technically feasible [40, 41]. Another problem could
reside in the security aspect of the application, as it
logs sensitive information about ones daily life and
thus needs special protection.
The application translates the amount and cost into
machine-readable numbers, which then can be further
processed automatically by the smart device. By the
combination of actual consumption of fuel and
movement data we have a very detailled description of
power usage for private mobility. Accelerometer date
can be used to further refine the accuracy of
measurement.
By combining home and mobility energy usage: data
gathering and storing, an appealing and intelligently
designed interfaces to provide instantaneous feedback,
we are able to interfere common habits and shape
decisions towards a more rational and normative
choice in favour of the environment.
An alternative option to OCR could be a QR-code on
the bill you receive when refueling. On the positive
side we would have a physical reminder, but for this
solution we need a third party to cooperate, plus we
wouldn't be able to cover customers which have
monthly bills.
7
1.
For the remaining transportation means – public
transport, biking and walking – they would be covered
by GPS and estimated energy usage, as they cannot be
measured accurately.
2.
3.
4.
The user-interface would be able to show electricity
and mobility, a simple power gauge at default but
detailled on an per device level on demand.It would be
geared towards an intuitive yet powerful surface, which
hides all device based details unless wanted.
5.
6.
7.
8.
9.
10.
With this setup we cover the two major energy
consuming sectors and lower the barrier of data
gathering significantly. Further incentives for
continued data collection might be given by add-on
services which use the collected data and compare it
with other users to compete for fun [39, 42]. An
adaptive gas algorithm could itself remind of a low fill
level and connect to an online service to indicate cheap
fuel station on the route nearby.
11.
12.
13.
14.
15.
16.
17.
18.
19.
43
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44