THE MOTIVE CONCEPT
Enabling Mobile Terminals to Act as Sensors
Michael Masikos, Konstantinos Demestichas, Evgenia Adamopoulou
School of Electrical Engineering and Computer Science, National Technical University of Athens, Heroon Polytechneiou 9,
Zographou, 15773, Greece
Christos Desiniotis
Vodafone-Panafon S.A., Tzavela 1-3, Chalandri, Athens, 15231 Greece
Keywords: B3G environment, End User Experience, Positioning Techniques, Ubiquitous Monitoring, Wireless Sensor
Networks.
Abstract: In a mobile telecommunications environment, the mobile terminal collects a variety of network performance
related data that are subsequently used in order to perform basic networking functions, such as cell
selection, handover or power control. Terminals’ processing capabilities and the potentials derived through
their integration with sensors, remain today mostly untapped. Taking advantage of these evolving sensing
capabilities, the MOTIVE (MObile Terminal Information Value addEd Functionality) project intends to
demonstrate the potential stemming from the exploitation of such information. The MOTIVE system
comprises a terminal monitoring module (which operates in a user transparent mode) and a network module
that collects the appropriate set of data and performs the proper processing. The paper examines the
application of this concept in three key areas, related to integrated end-to-end user experience monitoring,
ubiquitous terminal assisted positioning and anonymous mobile community services, taking into account the
terminal functionality evolution as well as the network evolution towards a multi-access composite IP based
network.
1 INTRODUCTION
Recent evolutions in mobile communications
include both the widespread use of mobile terminals
and the development of new technologies. Indeed,
more than 2 billion people around the globe are
mobile communications subscribers, and growth
rates are considerably promising for the future. In
addition, modern mobile terminals have become
technologically sophisticated, encompassing
increased functionality and a variety of extra
features, such as cameras, multiple antennas,
temperature sensors, and short range connectivity
(e.g., Infrared and Bluetooth).
In parallel, the scientific community has recently
shown a tremendous interest in the area of wireless
sensor networks. Significant progress has been
made, regarding sensors’ hardware, operating
systems, embedded software, and networking
enabling technologies. As a result, modern wireless
sensor networks have provided the means for
developing innovative applications, targeted for
environmental monitoring, motion monitoring as a
form of condition-based maintenance (Culler et al,
2004), patient monitoring and assisting (Jovanov et
al, 2001), inventory management, product quality
monitoring and disaster areas monitoring. Hence, the
use of wireless sensor networks is valuable for a
variety of applications and is expected to grow
further in the future.
In this paper, it is argued that the largest wireless
sensor network existing today is the community of
mobile terminals, which still remains unexploited.
Indeed, mobile phones and sensors present a lot of
similarities:
(a) relatively limited processing speed and
storage capacity;
(b) substantial processing capability in the
aggregate, but not individually; and
(c) wireless communication capability.
347
Masikos M., Demestichas K., Adamopoulou E. and Desiniotis C. (2006).
THE MOTIVE CONCEPT - Enabling Mobile Terminals to Act as Sensors.
In Proceedings of the International Conference on Wireless Information Networks and Systems, pages 347-354
DOI: 10.5220/0002094003470354
Copyright
c
SciTePress
What is more, mobile terminals present a number
of useful characteristics. Firstly, in contrast to sensor
nodes, mobile phones have a global identification
(ID), the Mobile Station International ISDN Number
(MSISDN). Secondly, there are already a large
number of devices scattered all over the world.
Thirdly, the location of these devices can be
estimated via a number of indoor and outdoor
localisation methods (Muthukrishnan et al, 2005).
Consequently, a “sensor network” consisting of
mobile terminals can provide applications with
geospatial data at a higher granularity and with
greater coverage than previously possible.
The MOTIVE (MObile Terminal Information
Value addEd Functionality) project introduces the
aforementioned innovative idea, which has not yet
been exploited. Mobile phones collect by default
several measurements, concerning, for example, the
bit error rate and the signal-to-noise ratio, which are
subsequently used in order to perform basic
networking functions, such as handover. These
measurements are currently untapped, in the sense
that they are not fully exploited. Moreover, mobile
phones could be outfitted with several inexpensive
sensors that provide enhanced capabilities.
Based on this idea, MOTIVE’s vision is to build
a powerful wireless sensor network. MOTIVE
enabled terminals are expected to transparently
store, pre-process and upload monitored data to the
network, without, however, obstructing the user
from utilising his device. In more detail, the
MOTIVE project proposes the application of this
innovative “sensor network” in three key areas,
related to: (a) integrated end-to-end user experience
monitoring; (b) ubiquitous terminal assisted
positioning; and (c) anonymous mobile community
services.
This paper describes the architecture of the
MOTIVE concept and the proposed applications in
the three key areas. Section 2 presents the proposed
architecture regarding the terminal and the network
side. Sections 3, 4 and 5 refer, in detail, to the three
proposed applications, as well as the methods in
which the capabilities of the underlying network can
be exploited. Finally, Section 6 concludes the paper
and identifies future research directions.
2 THE MOTIVE
ARCHITECTURE
2.1 Network Architecture
A high level presentation of MOTIVE’s proposed
architecture is depicted in Figure 1.
As can be observed, two main entities comprise
the overall system: (a) the data capturing devices;
and (b) the network server. Communication and data
transferring between these entities is carried out by
exploiting a composite radio network infrastructure,
consisting of diverse, heterogeneous networks.
External
sensor
GSM, GPRS
UMTS
WLAN
WiMax
MOTIVE
Server
A
P
I
s
Service
Providers
Integrated
sensor
Figure 1: MOTIVE high-level architecture.
The data capturing devices fall into three
categories: (a) external sensors communicating with
the mobile terminal and transferring the collected
data to it through a short-range technology (e.g.,
Bluetooth); (b) sensors integrated to the mobile
terminal; and (c) the mobile terminals, acting as
sensors themselves.
Regarding (a), external sensors are devices
equipped with simple networking functionality and
able to sense different environmental parameters.
Their size or power consumption, however, does not
permit their integration to the mobile terminal. A
typical example of this type of sensors is the gas
sensors (Schmidt et al, 2001). These sensors require
a significant amount of time for heating up,
accompanied by excessive energy consumption
(often around 1W for 1 minute).
Pertaining to (b), there are sensors that their
energy demand, processing requirements and size
render their integration to the mobile terminal
feasible. In fact, a number of mobile devices already
implement such sensing abilities. For example,
microphones can provide valuable information, even
WINSYS 2006 - INTERNATIONAL CONFERENCE ON WIRELESS INFORMATION NETWORKS AND SYSTEMS
348
when using minimal processing power.
Calculations on a microcontroller with less than 200
bytes of RAM proves to contribute useful
information, such as the noise level and the type of
input (noisy, music, speaking).
Concerning (c), mobile terminals can act as
sensors without any extra enhancements. In other
words, the mobile terminal can record and upload
measurements of parameters related to its operation,
as, for instance, the perceived signal strength. This
information can later be used in a plethora of
applications, like location based services.
In order for these captured data to be efficiently
exploited, their further processing is required.
Initially, the data collected are pre-processed at the
mobile terminal. The pre-processed data are then
uploaded to the MOTIVE application server through
the radio access interface used by the terminal. The
scheduling of the transmissions and the cost of
transferring the data are matters that need to be
carefully examined before deploying the
corresponding services. The main volume of the
required processing is conducted by the MOTIVE
server. Appropriate functionality for retrieving,
indexing and storing the collected information is in
place in this entity. Service providers should be able
to retrieve the necessary information through
suitable Application Programming Interfaces.
2.2 Definition of Functional Layers
In what follows, a layered architecture is presented,
serving as the basis for the development of a simple,
yet efficient, system aiming at the provision of
enhanced, context-aware applications. The four
layers comprising the proposed architecture are
depicted in Figure 2. For further comprehension of
the system’s functionality, the role of every layer
will be discussed, and a representative application
will be investigated.
The lower level consists of the data capturing
devices, namely the three abovementioned types of
sensors. These components are responsible for
collecting the required measurements from their
surroundings and, in the case of the external sensors,
transmitting them to the mobile terminals.
The next level involves the formation of cues. By
using the term cue (Schmidt et al, 2001), we refer to
information that has been submitted to a pre-
processing procedure. The concept of cues has
proven to be very useful, since it provides a level of
abstraction from the hardware components and
renders their modification transparent to the higher
layers. In this way, if new sensing devices are
included in the system, only changes to the
corresponding cues must be adapted. Cues can be
realized by using appropriate statistical functions.
Thus, the collected data are either summarized or
processed at a basic level. Typical examples of cues
that are usually investigated are the average value,
the standard derivation and the first derivative. It is
Data Capturing Level
Data Capturing Level
Sensor #1
Cue
1.1
Cue
1.2
Cue
1.3
Sensor #1
Cue
1.1
Cue
1.2
Cue
1.3
Sensor #2
Cue
2.1
Cue
2.2
Cue
2.3
Sensor #2
Cue
2.1
Cue
2.2
Cue
2.3
Sensor #3
Cue
3.1
Cue
3.2
Cue
3.3
Sensor #3
Cue
3.1
Cue
3.2
Cue
3.3
Cue Level
Cue Level
Content Formation
Content Formation
Level
Level
Application
Developer
Application
Developer
Application
Developer
Applications Level
Applications Level
Content
Content
Figure 2: Functional layers of the MOTIVE architecture.
THE MOTIVE CONCEPT - Enabling Mobile Terminals to Act as Sensors
349
noteworthy that each cue is dependent on one single
sensor, but, by using the data of one sensor, multiple
cues can be calculated.
The next level involves the formation of content,
that is the main processing and indexing of the
collected information into organised structures. The
result of this level’s processing leads to data forms
that can be directly exploited by the application
providers of the higher level.
Finally, at the top of the proposed architecture
lies the application level. All possible context-aware
applications utilizing the collected information can
be included in this level.
Taking into account the processing capabilities
of the mobile terminals, the power consumption
limitations raised, as well as the network load
provoked, the following mapping of the functional
entities described above to the network entities of
Figure 1 can be deduced: Data retrieval from sensing
devices and cue development can be integrated in
the terminal-side. More precisely, the MOTIVE
terminals will gather the desired information and
proceed in its statistical pre-processing. This
information will afterwards be uploaded to the
MOTIVE server, where it will be submitted to the
content formation procedures. The content created
by these procedures will then become available to
application developers through the appropriate
interfaces.
In what follows, a simple, yet enlightening,
application will be presented, through which the
functionality of the involved entities will be
clarified. This application is launched by a service
provider who desires to deploy a service providing
temperature information over a large city. Firstly, at
the lowest level, mobile terminals, integrating the
temperature measurement functionality, will record
temperature values, perceived at their current
positions. These measurements will then be pre-
processed by the mobile terminal, in order to form
the corresponding cues. Useful and exploitable
parameters would be, for example, the average
temperature and the corresponding changing rate.
The time window during which the measurements
should be taken is a matter of further study. The
results are then uploaded to the MOTIVE server. At
this point, they are combined with measurements
originating from other terminals, and the main
volume of processing takes place. A useful piece of
information, resulting from this level, would be, for
example, the categorization of the perceived
temperatures, according to the specific time and
place they were measured. Finally, at the higher
level, the application provider would exploit this
formatted content, in order to create maps of the area
under consideration, where measured temperatures
would be depicted in a user-friendly way (e.g.,
different colours indicating different climate
conditions).
3 END-TO-END USER
EXPERIENCE MONITORING
As has already been noted, in a mobile
telecommunications environment, the mobile
terminal collects a variety of network performance
data that are subsequently used in order to perform
basic networking functions, such as cell selection,
handover or power control. Terminal collected data
constitute a valuable, but untapped yet, source of
information. By properly exploiting them, mobile
terminals can turn into ubiquitous super-sensors,
providing information about end-to-end user
experience.
In more detail, the integration of a monitoring
agent will enable mobile terminals to monitor
several Key Performance Indicators (KPIs), related
to: (a) the efficiency of the user interface; (b) the
efficiency of the protocol stack during
communication; and (c) the network’s performance.
Regarding (a), the time it takes to find and
trigger an application through the user interface, as
well as how often an application is used, can be
assessed. Pertaining to (b), several parameters,
including the receiver quality, the voice quality and
the IP protocol performance, can be utilized. Both of
the aforementioned issues are currently addressed
via terminal testing, which lacks in scalability.
MOTIVE’s monitoring agents can complement to
the task of terminal evaluation, helping terminal
manufacturers to improve their products.
Concerning (c), the contribution of network
performance to user experience can also be assessed
at the level of the mobile terminal, by measuring
primarily air-interface parameters related to
coverage quality and air-interface performance,
including the bit error rate and the signal-to-noise
ratio. By acting, in this way, as sensors and relaying
the aforementioned measurements back to the
network side, possibly after some filtering or pre-
processing (e.g., calculation of the average value),
mobile terminals can provide significant feedback to
mobile network operators, in issues such as radio
planning and customer care. Currently, to resolve
these issues, mobile network operators rely on
network verification surveys, KPIs derived from the
WINSYS 2006 - INTERNATIONAL CONFERENCE ON WIRELESS INFORMATION NETWORKS AND SYSTEMS
350
Network Management Systems (e.g., blocked or
dropped calls), or measurements from special
terminal implementations, such as Ericsson TEMS
and Nokia Traffica. The MOTIVE approach is able
to outperform the state-of-the-art, as it is far more
scalable and collects measurements from the actual
end users.
In addition to the benefits for terminal manufacturers
and mobile network operators, the MOTIVE enabled
terminals can prove to be valuable for context radio
systems. Cognitive radio systems can be defined as
systems capable of sensing the RF environment and
easily adjusting to current conditions, by making
intelligent decisions about how to best utilize
spectrum. In this context, mobile terminals can act
as sensors, in order to properly “sniff” the RF
environment and detect spectrum holes, i.e. RF
bands where the interference level is below a certain
threshold, rendering them usable for communication.
The collection of measurements for this purpose and
the use of a feedback channel, so as to transfer them
to the network side, can facilitate the latter to select
the most suitable configuration, at any given time.
4 UBIQUITOUS TERMINAL
ASSISTED POSITIONING
Various research activities are ongoing in the field
of Location Based Services (LBS), a type of services
that is expected to give a boost to mobile
communications. The provision of such services
assumes that the position of the client is known.
Hence, localisation proves to be of paramount
importance for their development.
Several techniques have been proposed for
addressing the localisation problem. These
techniques can be classified according to several
characteristics (Muthukrishnan et al, 2005):
Outdoor vs. Indoor, depending on the
position area.
Network based vs. Terminal based,
depending on the side of the implementation
(terminal or network).
Terrestrial-radio-based vs. Satellite-based vs.
Standalone depending on the use of a
terrestrial radio signal, a satellite signal or no
use of signal for positioning.
According to the location estimation
technique used, namely Global Positioning
System (GPS), Assisted GPS (A-GPS),
Observed Time Difference (OTD), Time of
Arrival (TOA), Time Difference of Arrival
(TDOA), Angle of Arrival (AOA), Multipath
Fingerprinting, Timing Advance (TA),
Enhanced Forward Link Triangulation (E-
FLT) and Received Signal Strength (RSS).
All of the aforementioned positioning methods
rely on signal measurements. In some cases, the
measurements are collected by a mobile device
acting as a sensor, while in other cases by a
specialised sensor network that may or may not
cooperate with a mobile device. Regarding the
specialised sensor networks, several techniques have
been proposed so far, based on Bluetooth (Forno et
Figure 3: The UTAP architecture.
THE MOTIVE CONCEPT - Enabling Mobile Terminals to Act as Sensors
351
al, 2005), Ultra Wide Band (UWB) (Bocquet et al,
2005), Infrared (Lee et al, 2004), Ultrasonic (Holm
et al, 2005), GPS (Zhao, 2002), or force measuring
sensors (Orr at al, 2000).
All of these techniques can easily be integrated
in the Ubiquitous Terminal Assisted Positioning
(UTAP) concept, which is illustrated in Figure 3.
The main characteristics of the UTAP concept
are:
It is functional in a B3G environment, where
a variety of network technologies (GSM,
GPRS, UMTS, WLANs, short range radio
interfaces, etc.) are present.
It can use any of the existing positioning
methods and techniques, either as a stand-
alone or as a hybrid scheme.
The use of A-GPS is proposed for positioning
in RF-shadowed environments. The basic
idea of assisted GPS (Zhao, 2002) is to
establish a GPS reference network whose
receivers have clear views of the sky and can
operate continuously. The most important
contribution of a reference network to
handset GPS receivers is the reduction of the
frequency uncertainty of satellite signals.
The Statistical Terminal Assisted Mobile
Positioning (STAMP) (Markoulidakis et al,
2006) approach can utilize the terminal’s
historical positioning data, in order to
improve the terminal positioning accuracy.
STAMP exploits the measurements that the
mobile terminal periodically collects while in
idle mode. Firstly, standard positioning
techniques are applied on the collected
measurements to provide estimations of the
terminal’s positions in successive time
moments. Then, statistical filtering (e.g.,
Kalman filter) is applied on the latter
estimations, in order to accurately infer the
terminal’s current position.
It allows the concurrent estimation of the
mobile terminal’s speed and direction,
enabling the timely provision of advanced
LBS applications.
It requires only an additional software
module on the terminal side, while the impact
on the terminal operation is minimal (e.g.,
through the exploitation of parameters which
terminals anyhow measure as part of their
standard operation).
Based on these characteristics, the UTAP
concept intends to provide location estimation under
any circumstances and with high precision. Further
research and real experiments for evaluation
purposes are ongoing under the MOTIVE project.
5 ANONYMOUS MOBILE
COMMUNITY SERVICES
The MOTIVE concept allows for the definition of a
new, innovative type of services, the Anonymous
Mobile Community (AMC) services, which exploit
the capability of the terminals to act as sensors, i.e.
collect information, and present it to the network
whenever required.
Figure 4 depicts the concept of MOTIVE AMC
services. According to this notion, the service
requestor may be either a third-party application
server or a mobile terminal. The MOTIVE AMC
server receives and validates the request, and
produces a response. Depending on the type of
service, there are two alternatives for generating the
appropriate response: (a) the real-time approach; and
(b) the non real-time approach.
Anonymous Mobile
Community
Motive
Terminal
Module
Motive
Terminal
Module
Motive
Terminal
Module
B3G Heterogeneous
Access Network
MOTIVE Anonymous
Mobile Community
(AMC) Server
B3G Composite Core
Network
Mobile
Terminal
Third-party
Application
Server
Figure 4: The concept of MOTIVE Anonymous Mobile
Community Services.
In (a), information is collected from the
community of terminals immediately after validating
the service request. Then, this information is
processed, and the appropriate result is sent back to
the requestor. In (b), the MOTIVE AMC server
generates a response on the basis of the data that
have already been collected from the community of
terminals. In all cases, user anonymity and privacy
should be respected. Privacy considerations are of
high importance, and the relevant requirements, as
WINSYS 2006 - INTERNATIONAL CONFERENCE ON WIRELESS INFORMATION NETWORKS AND SYSTEMS
352
specified in (3GPP, 2002) and (3GPP, 2005), must
be satisfied.
Viewing an anonymous community of mobile
terminals as a grid of active sensors offers the ability
to construct a group of useful, innovative services on
top of it. Representative examples of interesting
services are depicted in the following.
(a) Environmental services. In this case, each
terminal belonging to the anonymous community
will provide information about the current
temperature and the weather in its position.
Requestors (either third-party application servers or
terminals that are members of the community) can
be informed about the average temperature and
climate conditions in the area of their interest.
(b) End-user experience monitoring. As
described in Section 3, the anonymous community
of terminals can be used to sense KPIs, such as the
bit error rate and the signal-to-noise ratio. Mobile
network operators act in this case as requestors.
(c) Electromagnetic field monitoring. In a
similar way to (b), terminals belonging to an
anonymous community may be utilized to measure
the value of the electromagnetic field in the used
frequency bands. Special non-profit organizations
will act as requestors, and generate reports about
whether safety levels are met or not.
(d) Traffic conditions monitoring. The retrieval
of road traffic conditions from fellow drivers
(determined by the terminal velocity in that area),
who are subscribers to the corresponding
anonymous community, can prove to be extensively
valuable in modern cities. Third-party application
servers or terminals that are members of the
corresponding community can act as requestors.
In general, provided that privacy requirements are
satisfied in an uncompromised manner, this type of
services is expected to become more and more
popular in the future.
6 CONCLUSIONS
In this paper, the concept of enabling mobile
terminals to act as sensors, by collecting data from
their RF and physical environment, was evolved.
The exploitation of such information in three key
areas, related to integrated end-to-end user
experience monitoring, ubiquitous terminal assisted
positioning and anonymous mobile community
services, was established.
Further research activities include the detailed
specifications and development of the corresponding
applications, as well as the conduction of trials for
the evaluation of the system’s functionality. The
trials will be performed using commercially
available mobile terminals in two different sites,
Athens and Paris, employing several diverse radio
access networks.
ACKNOWLEDGEMENTS
This paper introduces concepts and technologies
deployed within the framework of the project
MOTIVE (FP6-IST-27659), which is co-funded by
the European Commission in the 6th framework of
the IST program.
REFERENCES
3GPP TR 23.871 V5.0.0, 2002. Enhanced support for User
Privacy in location services. Release 5.
3GPP TS 23.271 V7.3.0, 2005. Functional stage 2
description of Location Services (LCS). Release 7.
Bocquet, M., Loyez, C., Benlarbi-Delaϊ A. (2005). Using
Enhanced-TDOA Measurement for Indoor
Positioning. In IEEE Microwaves and Wireless
Components Letters, Vol. 15, Issue 10, 612 - 614.
Culler, D., Estrin, D., Srivastava, M. (2004). Overview of
Sensor Networks. In IEEE Computer’s Society
Magazine, Vol. 37, Issue 8, 41 - 49.
Forno, F., Malnati, G., Portelli G. (2005). Design and
implementation of a Bluetooth ad hoc network for
indoor positioning. In Software Engineering, IEE
Proceedings, Vol. 152, Issue 5, 223 - 228.
FP6-IST4 27659 MOTIVE Technical Annex.
Holm, S., Hovind, O., Rostad S., Holm, R. (2005). Indoor
Data Communications using Airborne Ultrasound. In
IEEE ICASSP.
Jovanov, E., Raskovic, D., Price, J., Chapman, J., Moore,
A., Krishnamurthy, A. (2001). Patient Monitoring
Using Personal Area Networks of Wireless Intelligent
Sensors. In Biomedical Sciences Instrumentation.
Lee, C., Chang, Y., Park, G., Ryu, J., Jeong, S., Park, S.,
Park, J., Lee, H., Hong, K., Lee, M. (2004). Indoor
Positioning System Based on Incident Angles of
Infrared Emitters. In the 30th Annual Conference of
the IEEE Industrial Electronics Society, Vol. 3, 2218 -
2222.
Markoulidakis, J., Desiniotis, C. (2006). Statistical
Terminal Assisted Mobile Positioning in a Beyond 3G
Environment. In the 15
th
IST Mobile & Wireless
Communications Summit.
Muthukrishnan, K., Lijding, M., Havinga, P. (2005).
Towards Smart Surroundings: Enabling Techniques
and Technologies for Localization. In LoCA
Proceedings. Vol. 3479. Springer-Verlag.
THE MOTIVE CONCEPT - Enabling Mobile Terminals to Act as Sensors
353
Orr, R., Abowd, G. (2000). The smart floor: a mechanism
for natural user identification and tracking. In
Conference on Human factors in computing systems.
Schmidt, A., Karlsruhe, U., Laerhoven, K.-V. (2001).
How to build smart appliances. In IEEE Personal
Communications, Vol. 8, Issue 4, 66 - 71.
Zhao, Y. (2002). Standardization of Mobile Phone
Positioning for 3G Systems. In IEEE Communications
Magazine Vol. 40, Issue 7, 108 - 116.
WINSYS 2006 - INTERNATIONAL CONFERENCE ON WIRELESS INFORMATION NETWORKS AND SYSTEMS
354