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Intelligent Systems Group (ISG)
Professor Juha Röning, Professor Jukka Riekki and Professor Tapio Seppänen,
Computer Engineering Laboratory, Department of Electrical and Information Engineering, University of Oulu
juha.roning(at)ee.oulu.fi, jukka.riekki(at)ee.oulu.fi, tapio.seppanen(at)ee.oulu.fi
http://www.ee.oulu.fi/research/isg
Background and Mission
The Intelligent Systems Group's (ISG) mission is to
carry out long-term research on novel technologies and
applications of intelligent systems. The main objective is to
develop enhanced adaptivity and context-awareness for
smart environments. The research specifically focuses on the
creation of dynamic models that enable monitoring,
diagnostics, prediction and control of target systems (living
and artificial) or operating environments. It is our aim to
make the environment adapt to the users, instead of making
the users adapt to an inflexible environment. We believe
that by creating these novel components for smart
environments, important enabling functionality will emerge that will
multiply the versatility and applicability of such living
environments.
We see behaviour modelling as a major challenge in
developing truly intelligent and proactive environments.
Human users of smart environments often behave in such a
complex manner that it is hard to predefine and pre-program
all of their behavioural patterns in the software. Models of
user behaviour are required that are able to grasp the user's
context at any moment, and to enable adaptation of the
functionality of the intelligent environment to the situation
at hand. Further, it is essential to model the behaviour of
the devices controlled by the intelligent environment, as
this enables adaptation to environmental changes without
reprogramming. Systems should eventually learn and
adapt automatically through these models to perform their
duties effectively.
Our research group combines a variety of key skills
and technologies to aim at this goal. We have experience in
the following key technologies: system architectures and
implementation of context-aware systems; modelling and
recognition of contexts from sensor signals; data
mining algorithms; learning nomadic robots; embedded
systems technologies; software security; and smart
environment implementations. The key application areas are: smart
living environments in homes and institutes; industrial
automation; mobile robots; context-aware mobile devices;
and wellness and medical applications. Each of these
domains possesses special characteristics, but, from the point of
view of developing algorithms for an intelligent system, they
also possess remarkable similarities. They all produce a
multitude of signals that represent the status of the system.
The target system behaviour should be modelled and
recognized from the signals. The application service should then
act accordingly. The availability of several application
domains yields many advantages: a solution to a special problem
in one domain may offer added-value functionality in
some other domain; our solutions are deployed by many of
our client industries; solutions to a wide range of
real-world problems define a credible and versatile tool-box that has
a major impact on our development-oriented
sub-contractual projects.
The group co-operates with many international and
domestic partners. In applied research, the group is active in
European projects. The group hosted three large
European project meetings (ROBOSWARM, XPRESS,
eConfidential) in 2008. In addition, several joint projects are funded
by the Finnish Funding Agency for Technology and
Innovation (Tekes) and industry.
The group and its members are active in the scientific
community. For example, Prof. Juha Röning co-chaired
numerous international workshops in the software security
area: The 9th Winter School of the European Intensive
Programme on Information Security Management and
Technology (IPICS) was arranged in Rovaniemi, and the
4th Crisis Management Workshop (CRM 2008) in Oulu,
Finland. In information security, the group acted as a
member of the SAFECode International Board of Advisors,
2008. The group also coorganized a Vulnerability Prevention
and Software Security seminar with a keynote speech by
Mr. Howard Schmidt in April, 2008.
Prof. Tapio Seppänen is a leading figure in both the
WellTech Oulu Institute, and the Oulu School of Biomedical
Engineering, an umbrella organization of wellness and
medical technology education at the University of Oulu and the
Oulu University of Applied Sciences.
Several members of the group were also on the
committees of international conferences. The group's expertise is
recognized, testified by the many invited talks and
lectures that have been given. The Intelligent Systems Group
has communicated its research to the public and its
research areas have attracted interest in the media.
In 2008, the research at ISG concentrated on
prototyping smart environments, mobile and context-aware systems,
data mining methods, signal analysis and secure
programming. These were applied in context-aware mobile systems,
intelligent service robots, quality control of steel plant
and spot welding processes, and analysis of biomedical
ECG and EEG signals.
Verification of the developed methods and models in
prototypes will be an important part of the research. To
support this activity, we will develop software and
hardware architectures for smart environments. In addition to
verification, prototypes speed up the commercialization of
the research results. In prototyping, we have set and
tackled the following objectives:
Developing hardware architecture for a smart
environment. The aim is to develop a basis for devices operating in
a smart environment. Modular technologies have been
the subject of our research for some years now. Modularity
has been achieved using a modular electronic concept,
the Embedded Object Concept (EOC) Atomi and a
modular software architecture - Property Service -, which
provides an interface for these resources, and an opportunity to
control different robots and other devices of a smart
environment.
EOC is a concept that utilizes common
object-oriented methods used in software by applying them to
combined Lego-like software-hardware entities. These modular
entities represent objects in object-oriented design
methods, and they function as the building blocks of embedded
systems.
This concept enables one to build new embedded
systems from electronic Lego-like building blocks. The goal of
the EOC is to make designing of embedded systems faster
and easier while preserving the commercial applicability of
the resulting device. The EOC enables people without
comprehensive knowledge in electronics design to create
new embedded systems. For experts, it shortens the design
time of new embedded systems. Implementing the
conceptual idea of embedded objects has been successfully
implemented with the Atomi II framework.
The EOC research has proceeded by developing new
objects. The focus of the research has been on improving
their robustness, and testing the concept in practice by
supporting other research projects. The research will continue
towards user friendly development tools in order to
further improve the concept.
Localization is one of the fundamental problems in
mobile robotics, as in many applications a robot needs to know
its location in order to perform its tasks. A global
self-localization technique was proposed that utilizes observations
of the ambient magnetic field. This study was inspired by
evidence that animals use the magnetic field of the Earth
for true navigation. The experiments reported in this
article suggest that (especially) modern buildings with
reinforced concrete and steel structures have unique spatially
varying ambient magnetic fields that can be used for navigation,
in very much the same way as the Earth's magnetic field,
but on a smaller scale. In principle, a non-uniform
ambient magnetic field produces different observations,
depending on the path taken through it. The approach provides a
promising and simple technique for solving the global
indoor self-localization problem.
The current technique is applicable for a
one-dimensional localization problem, i.e., for localizing a robot or a
person within corridors. However, the proposed approach
could be extended to two- or three-dimensional localization
problems, assuming that maps can be provided. In some
applications, the proposed approach may provide an
alternative to machine vision based approaches, especially when
only one-dimensional localization is needed, or when the
illumination of the environment changes. On the other
hand, the proposed technique may also be used in parallel
with machine vision and range finder based approaches in
order to overcome possible sensor aliasing problems.
The experiments suggest that the ambient magnetic
field may remain sufficiently stable for longer periods of time.
In the conducted experiments, the magnetic field
remained nearly unchanged, although some variations were
observed. These variations did not, however, have a great impact
on the localization performance. On the other hand, the
magnetic field is not sensitive to many environmental
changes that may affect other localization techniques, such as
vision or range finder based techniques which rely on
visual or geometrical features. For example, the magnetic field
is not sensitive to non-magnetic dynamic or static objects,
nor to changes in illumination.
Two-dimensional magnetic map in a corridor of the Computer Engineering Laboratory, and the measurement system used in global self-localization experiments.
Multi-robot exploration methods can be utilized to
explore unknown environments using a team of robots. In ISG,
a novel multi-robot exploration algorithm has been
studied. The exploration algorithm chooses frontier cells for
each individual robot so that the overall exploration time is
minimized. The frontier cell is a cell between a known and
an unknown area. Whenever a robot arrives at the frontier
cell, new information is received around the cell. Each cell
of the occupancy grid map contains a probability that the
cell is occupied. The cell is occupied if the corresponding
area in the environment is covered by an obstacle. The only
requirement is that the map must allow the distinction
between known and unknown areas and it must compute
travel costs for the individual robots. The algorithm
simultaneously takes into account the cost of reaching a frontier
cell and its utility. The cost of the cell depends on the
occupancy probabilities of the cells along the path of the
robot, and the distance between the robot and the cell.
Whenever a frontier cell is assigned to a robot, the utilities of the
nearby cells are reduced. The utility of the frontier cell also
depends on the number of robots moving near to the cell.
Our results suggest that this coordinated multi-robot
exploration technique is more effective than uncoordinated
techniques, as is shown below.
Paths of the robots in a coordinated case; the occupancy map produced by a team of coordinated robots; paths of the robots in an uncoordinated case; and the corresponding occupancy map.
Path optimization is a very important aspect of
multi-robot systems in which the available resources, such as
battery life, can be limited. Many real-world multi-robot path
optimization problems can be restated as an instance of
the Multiple Travelling Salesman Problem (MTSP). A
novel ant colony based algorithm called TACO was proposed
for solving the MTSP with a min-max objective. Its
competitiveness was shown by comparison to neural network
based approaches, and its feasibility in multi-robot systems
was demonstrated in a simulation environment.
TACO generated paths for two, three, and four robots in a hospital environment (top), and for three robots in the Computer Engineering Laboratory (bottom).
In autonomous environment modelling research we
sense the environment using mobile robots. This enables
selection of optimal sampling locations in order to provide
a model with maximum accuracy. In geostatistics
studies, optimal spatial sampling has traditionally focused on
the selection of sampling locations in advance. However,
with mobile sensors, we are able to select the locations based
on the current model which increases the accuracy of the
model and decreases the measuring time.
We have developed mobile sensing systems for
various environments, including indoor, outdoor, and aquatic
environments. In indoor environments, the most important
measured quantities are temperature, humidity, and
gas concentrations. In aquatic environments, measurements
on dissolved oxygen, pH levels, and temperature provide
important information for modelling these environments.
Our research integrates the latest results from geostatistics,
and multi-robot systems to enable implementation of fully
autonomous, and adaptive sensing systems.
A prototype of a robot boat for sensing aquatic environments: 1) an embedded computer with a WLAN communication interface, 2) sensors, and 3) GPS positioning system.
Context-aware services adapt to the user's situation.
We have studied context recognition in several different
application areas, including human physiology, wellness,
urban computing, smart office spaces and body sensor
networks. The aim is to find and develop methods for recognizing
the user's context from sensor data using signal
processing, pattern recognition and machine learning methods.
Context can be used to identify the services that are relevant
in the situation at hand - and to adapt these services.
During the year 2008, the research on context
recognition has continued with gesture recognition. We have
developed novel solutions and applied Hidden Markov models to
enable gestural controlling with an ordinary mobile
phone. The gestures are recognized from 3D acceleration
measurements that the N95 or Nokia Sport 5500 can
produce, but also other 3D acceleration sensor devices are
applicable. With the gestures, different applications can be
controlled, including the inner functionality of the mobile
phone. The gesture controller is configured with (gesture,
command, application) triplets. When the controller
recognizes a gesture, it sends the corresponding command to the
specified application. The system architecture is presented in
the following figure. The user can teach the gestures and
associate each gesture to a controlling command. For
example, a user can select a clockwise circle drawn in the air to
correspond to the command for opening the calendar
application on an N95. The second figure shows a user
controlling with gestures an application on a wall display. The
software was published as open source on November 2008
and it can be downloaded from the group's web site.
A user controlling an application on a wall display with gestures.
During the last year the group also studied recognition
of context from ambient audio. Here, audio from users'
everyday environments was recorded using a mobile
device, and through signal processing and classification, it was
used as a cue of the users' current context. Part of the work
was done in collaboration with Nokia Research Center and
MIT, and funded by the Fulbright organization.
The group is strongly moving on to studying signal
processing in networked sensing systems. The group members
are participating the UbiCity project, where a tool on
gathering, storing and processing sensor measurement from a
heterogeneous sensor network is being built. The group
has participated in organizing a data mining workshop
on sensorwebs, databases and mining in networked
sensing systems (2nd SWDMNSS 2008) together with Japanese
and German researchers. This workshop and several
two-way research visits with Tokyo Denki University's
Ubiquitous Networking Laboratory have created international
collaboration.
In addition to recognizing a user's context, sensor data
can be used to build a physical user interface in which a
user uses a mobile device as a physical object rather as a
traditional I/O device. The device is equipped with sensors
and the actions of the user are recognized from the sensor
data and interpreted as commands. Gesture controlling is
an example of a physical user interface; the user
commands the system by waving the terminal on the air. In addition
to gestures, the group is actively developing touch-based
physical user interfaces. These user interfaces are based on
RFID technology. An RFID tag storing service parameters
is placed behind an icon advertising a service. When a
user touches the icon with a mobile device that is equipped
with an RFID reader, the service parameters are read from
the tag and delivered to the system. Touch-based user
interfaces are an effective way of controlling a system, as
they produce rich contextual information: who requests a
service, which service, when, and where. With such interfaces, the user remains in control.
During 2008, the group developed several innovative
touch-based user interfaces in co-operation with the University
of Lapland. The group also developed further the
REACHeS platform that can be used to link physical user interfaces
to Internet services. The figure below presents a
touch-based user interface for controlling videos on a wall display.
At the bottom left we see an icon that advertises a service
in the environment, next to a wall display. When a user
touches this icon with a mobile device, a video is shown on the
wall display (top of the figure) and a remote control UI is
created on the mobile device's display (bottom right). The
users can now control the video on the wall display
using their mobile device Two alternative physical user
interfaces for the same service have been developed: Control
Panel and Control Cube.
A physical user interface for controlling videos on a wall display.
In addition, we created an application for sharing
information at our university's Zoological Museum. In this
application, icons are placed next to exhibition items, the
stuffed animals. Touching an icon with a mobile device brings
a list of item-related documents to the device's display.
The user can download the selected files to a device and
for example, listen the sound of an animal, or study a
photograph. Over 300 students from local primary and
secondary schools tested the application in spring 2008.
Biosignal Processing
Cardiovascular signal processing. Sudden cardiac arrest
is the most common cause of death in western countries.
It accounts for approximately 50% of cardiovascular
deaths, and apparently has a highly variable
pathophysiological etiology. The risk of sudden cardiac arrest is high in
certain subgroups of patients with a history of myocardial
infarction and depressed left ventricular function. The key
question in research is why do some subjects develop
ventricular fibrillation during acute coronary occlusion, while
others survive this episode without fatal arrhythmia. The
challenge for research is to develop approaches or techniques
that will allow the screening of the specific risk for fatal
ventricular arrhythmias as a predictor of the first event in
patient populations that have a low cumulative risk,
but generate a large number of victims. In addition, the
predictive value of many known risk factors of sudden
cardiac arrest among patients with known heart disease has not
been definitively established.
Invariant trajectory classification of dynamical systems
with a case study on ECG. An invariant pattern recognition
framework for classification of phase space trajectories of
nonlinear dynamical systems was developed. Using
statistical shape theory, known external influences can be
discriminated from true changes of the system. The external
effects are modelled as a transformation group acting on the
phase space, and variation of the trajectories not explained by
the transformations is accounted for using principal
component analysis. The approach suggested is highly adaptable to
a wide range of situations and individual differences.
The methodology presented is applied to detect
abnormalities in electrocardiograms. Results based on measured data
indicate that the model developed is resistant to the effects
of respiration and body position changes, which are
abundant in ambulatory conditions and cause significant
morphological artifacts in the signal. The results also show that
the detection of an artificially induced acute myocardial
infarction is achieved with high performance. Due to its
low computational complexity, the method developed can
be implemented in real-time. This method also adapts to
morphological changes caused by various heart conditions.
A method for estimating the severity of myocardial
infarction from multi-channel ECG. The measurement of
infarct severity is an important element in the overall care of
patients with STEMI (myocardial infarction with ST
segment elevation) patients. The severity of the MI (myocardial
infarction) is commonly estimated by cardiac biomarker
methods and echocardiography. We developed a method
for estimating the severity of the MI by combining an
action potential based computer model and 12 lead ECG
patient data. The estimators of the severity of the anterior and
inferior MI were developed using an EDL (equivalent
double layer) model. The best combinations of the single
parameter based estimators were found by using multiple
linear regression analysis. The correlations between the final
estimators and two clinical estimators of the severity of the
MI were calculated. The severity estimators correlated to
the maximum troponin value with r value 0.615 and to the
ejection fraction with r value 0.428. On the grounds of the
results, it is possible to calculate a coarse estimate for
the maximum troponin value, and therefore the severity of
the MI, from the standard 12 lead ECG by using the
simulation model based method. The estimated troponin value can
be used to yield a fast assessment of tissue damage of an
ambulatory cardiac patient that is suspected to have an
infarction.
Improving Reliability of `Total-Cosine-R-to T' (TCRT)
in Patients with Acute Myocardial Infarction. The
parameter TCRT (Total Cosine R-to-T) calculated from ECG
recording has been shown to have a remarkable prognostic
value as a predictor of the outcomes of coronary artery
disease and acute myocardial infarction (AMI) patients. The
TCRT is conventionally calculated using an algorithm
produced by Acar et al. (1999). In this study, the reliability of
the TCRT algorithm was tested with the ECG data of a
healthy group (n = 25) and the AMI group (n = 45). Typical
problems occurred in the detection of the maximum of the
T vector (9% of patients), the bounding of the R wave
(18%), a comprehensive segmentation (11%), and a decreased
congruence between TCRT and the spatial QRS-T angle
(33%). The results show that small improvements to the basic
algorithm can decrease the number of failures by up to
82% in AMI data. It is concluded that segmentation
properties should be improved in the basic TCRT algorithm in
order to maintain the diagnostic value of TCRT in different
patient data.
EEG signal processing. The aim of this task is to
develop new methods and algorithms for estimating the depth
of anaesthesia from a multi-channel EEG. A new concept
of relative induction time was recently developed by our
group, which enables a significant improvement in the depth
estimation from EEG. The new method produces a
time-continuous value for the depth estimate and accurately
predicts the instant of loss of consciousness. The method was
extended so that it can model the depth of anaesthesia to
such a depth that burst-suppression of EEG starts to evolve.
The team has so far focused on describing the spectral
characteristics of EEG related to the induction of anaesthesia
with propofol. The time-frequency characteristics of EEG
that are consistent between individuals during induction of
anaesthesia were determined. The relationship between
the EEG frequency progression pattern and the clinical
end-points, such as loss of obeying verbal command, was
shown. A mathematical method was developed for describing
the consistent EEG frequency progression pattern during
anaesthesia. The method has provided us the possibility
to study in detail the effects of analgesic drug
(remifentanil) on the EEG-based depth of anaesthesia estimation. The
results indicate that remifentanil modifies the relationship
of EEG spectral changes and clinical endpoints in
propofol anaesthesia. The effects of remifentanil on the onset of
burst suppression pattern were also presented.
EEG activity in different frequencies during induction of propofol anaesthesia.
Text production speedup technologies. The feasibility
of word prediction was studied in a highly inflected
language, Finnish, where words are used in many case forms, a
topic seldom addressed in the context of word prediction.
Since about one third of words will appear in uninflected
forms in Finnish, simple prediction methods, e.g. word
completion, typically employed in uninflected languages such
as English can be used as such in the prediction of
uninflected words. The preliminary results obtained show that
about 45% of characters can roughly be saved in Finnish
word prediction in general for uninflected words. Secondly,
the utility of predicting entire phrases instead of single
words, (as usually done in word prediction), consisting of two
or more words was investigated in English word
prediction. The results obtained show that about 70% of characters
of the phrases included in a lexicon of some 7,000 phrases
of legal English could be saved in theory when using the
best search key for their prediction.
Data Mining Systems
The focus areas of data mining research were
re-organised during the year 2008, and the research is now carried
out with a quite unique approach. The research challenges
are divided into three mutually supportive categories; the
research of algorithms producing knowledge, software running the algorithms and knowledge
bases storing the acquired knowledge. When put together, these three
categories form a strong combination which can be applied
to virtually any phenomena where data can be processed
into knowledge.
The research on algorithms was focused on advancing
methods for time series analysis, variance modelling and
novelty detection. Special interest was directed to
establishing data driven methods for these areas, where the exact
shape and nature of the observed data can be used to
characterize the phenomena under study. In software research, the
implementation of the first version of new software
architecture for running the algorithms came to
successful conclusion. The architecture presents the algorithms as
information generating logical devices to which the
information measuring physical devices connect. A
suitable combination of logical and physical devices can
thereafter be used to form a data mining software application.
In knowledge base research, the general ideas behind the
role of knowledge bases were established, and the
implementation of the first version of a concrete knowledge base
was carried to a successful end.
Three focus areas of the data mining research; algorithms generating knowledge, software running the algorithms and knowledge bases storing the acquired knowledge.
The research has focused on three projects, XPRESS
(2007 - 2010), SAMURAI (2006 - 2008) and MIDAS
(2008 - 2010). XPRESS is an integrated (IP) EU-project, where new
approaches for managing and optimizing the operation of
entire production facilities are being developed. In 2008,
data mining algorithms were created, for example, for
recognizing the tools the associates in the production lines are
using at a particular time. The analysis is based on
accelerometer data, and it can help, for example, in finding more
ergonomic ways of working. The software architecture
and knowledge bases were applied to storing the
generated knowledge in this application and also a wider range
of applications in factories.
The SAMURAI-project was completed during 2008,
and the results were evaluated to be so good that they gave
rise to the starting and granting of new funding for a
project, MIDAS, which is based on the results. In both
projects, methods for utilizing data originating from a steel
factory and human being were developed. The algorithms
applied to steel production helped in reducing the variability of
the quality of steel plates. Also, methods for pointing out
the right time to perform a production model parameter
update were reported. In the analysis of the human data,
methods for estimating the energy expenditure of various sports
exercises based on accelerometer data were reported for
the first time. Also, research for recognizing sport activities
from accelerometer time series was continued successfully.
The group had collaboration in the focus area of data
mining both internationally and nationally. The researchers
gave presentations of their results in 10 conference
presentations around Europe, the USA and Asia. Co-operation with
European researchers and industry was intensive also
thanks to the XPRESS project in which 17 different European
organizations are participating. The data mining group
also belongs to the Centre of Advanced Steel Research,
which is founded to gather together from both at home and
abroad steel research expertise at the University of Oulu.
At the end 2008, the future for data mining research
seems bright, and major advancements in all of the three
focus areas (algorithms, software and knowledge bases) can
be expected in 2009. International collaboration can be
expected to deepen even more during the next year thanks
to forthcoming long term research visits established in 2008.
In 2008, data mining methods were applied for example to monitoring tool usage of associates in production lines. The method could be used to improve worker ergonomics.
Within the Intelligent Systems Group, the Oulu
University Secure Programming Group (OUSPG) has continued
research in the field of implementation level security
issues and software security testing. Software implementation
may introduce potential for unanticipated and undesired
program behaviour, e.g. an intruder can exploit the vulnerability
to compromise the computer system.
In 2008, the research focus at OUSPG remained on
black-box methodology for improving software security.
OUSPG approaches the problem from three different
directions, namely, network traffic data-mining and visualization,
protocol genes and protocol dependence.
Causal relationships. The aim is to develop methods
for inferring causal relationships in complex systems. The
research applied data mining to network traffic to find
data relevant to the system being analysed. Applications of
the method include getting an overall view of the
communication patterns of complex systems, diagnostics and
security risk assessment.
Information network environments are more complex
than ever before, and the complexity will increase in the
future. One important factor affecting the increase in the
complexity is the convergence of information networks. One
seemingly simple event may generate a number of small
actions in different parts of the network. Additionally,
different components may use varying protocols. Thus the
secure development, deployment and management of
complex networks is laborious and requires in-depth
understanding of different fields.
Network traffic data mining research applies
black-box methodology in understanding the behaviour of
different components in computer networks. Examples of
systems where this work has been applied are operator
WLANs, firewalls and malware. Operator WLANs are a good
example of complexity due to the large amount of
infrastructure involved (e.g. integration with traditional phone
network authentication infrastructure). Firewalls may have
unintentional information leaks due to misconfiguration or
implementation problems. Malware is software that is
purposely obfuscated to make reverse- engineering and removal
difficult. By monitoring the external behaviour of malware, it
is possible to understand how it functions.
Identification of protocol genes. This research,
PROTOS-GENOME, approaches the problem of complexity from
the other direction, by developing tools and techniques for
reverse-engineering and identification of protocols based
on using protocol genes - the basic building blocks of
protocols. The approach is to use techniques developed
for bioinformatics and artificial intelligence. Samples
of protocols and file formats are used to infer structure
from the data. This structural information can then be used
to effectively create large numbers of test cases for this
protocol.
The PROTOS-GENOME project produced test suites
for several archive file formats that are typically
implemented, for example, in anti-virus products. The test suites
have been distributed to vendors in cooperation with
FICORA and NISCC. A number of vulnerabilities was found in
widely used antivirus software products. The method has been
also applied to find plagiarism in text.
Structural inference methods used in plagiarism detection.
As a continuation of OUSPG's practical security
research, work was conducted on the security of RFID systems.
This work is on-going in 2009.
Vulnerability management of the information
infrastructure contributes to protocol dependence. Another angle
on battling complexity is through technology
dependencies. This activity studies the impact factor of different
technologies on CNI, and develops a visual model for
understanding dependencies related to protocols. This
was accomplished by extending traditional Wikis, which
are effective mass collaborative authoring services
with graphing extensions. Graphingwiki enables deepened
analysis of the Wiki data by augmenting it with semantic data
in a simple, practical and easy-to-use manner.
Visualisation tools are used to clarify the resulting body of knowledge
so that only the data essential for a usage scenario is
displayed. Logic inference rules can be applied to the data to
perform automated reasoning based on the data. Perceiving
dependencies among network protocols presents an example
use case of the framework.
Practical RFID security research in progress.
A newly established area of research in OUSPG is
computer-assisted teaching. This work originated in 2005
with RAIPPA, software for automated software for
programming laboratory pre-exercises. Work on RAIPPA continued
in 2008 with funding from Campus Futurus, an
organization within the university that promotes the use of ICT in
teaching. The system has improved learning results
significantly, and it is currently being piloted with courses from
throughout the university.
The results of our research were applied to real-world
problems in many projects, often in collaboration with
industrial and other partners. Some examples of exploitation
are described below. Especially during the reported year,
outdoor robotics was a new area for exploitation of our
research results.
The Intelligent Systems Group utilizes a robotics
laboratory and pressure-sensitive floor (EMFi material)
installed in our laboratory as part of a smart living room. Other
equipment includes a home theatre, two degree-of-freedom
active cameras, four mobile robots and one manipulator,
a WLAN network, and various mobile devices (PDAs, a
tablet PC, Symbian mobile phones). WLAN positioning
covers a large part of the campus (including the
laboratory), and a home automation network is being installed. Our
aim is to gradually build a versatile infrastructure that
offers various generic services for pervasive applications.
Naturally, this kind of environment enables realistic
experiments that lead to a better understanding of such applications.
The embedded objects implemented according to the
Atomi II Framework specification are called Atomi objects. Several different Atomi objects have been created for real
life tests. The Atomi objects have been used in several
projects, and they have proved to be very usable.
The Atomi objects are being used both in pure
research projects and in projects that aim ultimately at
commercial products. The Atomi objects have been applied
to telepresence robots, nanoscale manipulation and
measurement technology, a hand held medical device, and
several robot applications. The most recent applications
include, for example, a micromanipulation platform and a bio
film measurement device.
The micromanipulation platform (shown below) is a
device platform that can be used for different
applications that require actuation and sensing in nanometer
resolution. Presently, nanoactuation devices on the market are very
expensive, and often limited in applications. This platform
is mostly built with off-the-shelf components and Atomi
objects, and thus brings about a reasonable cost for the
instrument.
Micromanipulation platform.
The device is based on a generalized modular
architecture which covers both device hardware and the control
software in a PC. The modular architecture enables a
swift changing of the actuators, sensors and tools with
minimal effort and reusable source code, thus being an ideal
frame for various applications.
The platform consists of a haptic 3D controller, a
piezoelectric actuator device, a probe and a PC. The haptic
3D controller enables manual control over the robot for
the user. The controller has a pen-like handle which can
be moved with six dimensions of freedom. The pen has
two buttons which can be assigned to different functions.
The controller also provides a haptic feedback option that
can be used to let the user feel what the robot feels.
The piezoelectric actuator device consists of three
linear piezo stages with position encoders. This actuator
moves the measurement. The device can be easily changed.
We have used a SmarAct piezo actuator, which can move in
a resolution of 5 nm in 3 cm range.
The probe (measurement head) is connected to the
actuator. It can be customized to every device separately. In
our test case, the probe is a silicon strain-gauge force
sensor AE-801, which is attached to mechanically custom
designed arm. The probe is connected to a voltage amplifier,
and further to AD-conversion on 24-bit precision AD
converter Atomi with USB and Power Atomi objects. A specially
designed needle is attached to the force sensor, to feel
the surroundings. In some applications the probe can
include an additional actuator. This actuator can be, for example,
a micro gripper, which also can be controlled via Atomi
objects.
A bio film measurement device measures the resistance of
a thin soft coating i.e. the bio film. This device is used
in measuring the properties of different type of coatings
for certain purposes. The thickness of the coating varies
between 1 µm and 2 mm. During the measurement, the
coating is on a level surface in a bowl filled with water.
The resistance is measured between a probe needle and the
surface that the coating is located on. The surface is a
plane made of material that conducts electricity. The needle
is 10 µm in diameter.
The measurement is not simple. In order not to damage
the bio film, the measurement current must be very low and
its polarity must constantly change. Otherwise the
sensitive surface may burn or otherwise get damaged.
Furthermore, the measurement must be made with several points on
the bio film in a reasonable amount of time. These
requirements demand an intelligent measuring method and
thus the programmable Atomi objects are very well suited
for the job.
The next figure shows the setup of the device. It consists
of several Atomi objects, the piezo actuators, the
measurement probe and a PC for the high level control and a UI for
the system. The Atomi objects that are in this device
include two PiezoLegs Atomi objects, a USB Atomi, a power
Atomi and an AD-DA converter measurement Atomi.
The results of the multi-robot and distributed sensing
research will be utilized in a real world application
scenario as a part of the ROBOSWARM project, which is an
EU project that was launched in November 2006. Together
with eight other participants, the University of Oulu has an
important role in this project, which aims to develop an
open knowledge environment for self-configurable, low-cost
and robust robot swarms usable in everyday applications.
Advances in the state-of-the art of networked robotics are
proposed through the introduction of a local and
global knowledge base for ad hoc communication within a
low-cost swarm of autonomous robots operating in the
surrounding smart IT infrastructure. For the ROBOSWARM
project ISG has developed a custom embedded control system
for the swarm of robots. The Sensor and Connectivity
Board (SCB) was designed with the aim of provide a modular
robot platform for swarm robotics research and
application development, where simplicity and modularity are
key-factors. The SCB is used to integrate all sensor modalities
and the motor control into one logical device, which can
be accessed through a USB port from any computer
having USB host capability. This solution providing easy access
to all sensors, and flexibility for selecting an embedded
host computer to perform the high-level data processing,
and motion control computing. The sensor set currently
supported by the SCB includes an RFID reader, sonars, a
laser range finder, 3-axis accelerometer, gyroscope, photo
diode, thermometer, humidity and atmospheric pressure
sensors, 3-axis magnetometer, and a real-time clock. SCB also
features a built-in interface to iRobot's Create mobile
robot, but it can easily be connected to any robot platform
with the UART connection. In addition, SCB provides
I2C, RS232, and SPI interfaces for adding new external
devices to expand the functionalities of the SCB even further.
An instrumented Robotic Team Member (RTM) built for the ROBOSWARM project.
During the reporting year, the group continued
utilizing outdoor robotic systems. Development and utilization
of Mörri, a multipurpose, high performance robot
platform continued, and major components for software
architecture were implemented. The software architecture further
developed the earlier work of Property Service
Architecture. The main focus of development has been on
multi-purpose control architecture, that can be used to integrate
various algorithms, methods and sensors to one real-time
system. Development of the robot included platform mechanic
design, high power brushless motor control electronics
and software, sensor integration, robot world modelling
and route reasoning user interfaces. The user interface is
designed for field use, including wearable control
devices, and use of Google Earth software for visualizing and
controlling the robot's global path.
The Group participated in the Military European Land
Robot Trial 2008, held in Hammelburg Germany in July.
M-Elrob is the biggest outdoor robot event in Europe,
and participants are research facilities and companies that
represent the state-of-the-art in Europe in this research
area. From four scenarios of competition, Mörri succeeded
in two, by winning the Camp Security scenario, and
getting fourth place in the Mule transportation scenario. In
October, the same Mörri platform was used in the
European Space Agency's Lunar Robot Challenge (Esa-LRC) held
in Teide, Tenerife. A new application module was
implemented, including a sampling device for soil samples.
The task in competition was to get samples from a 15 m
deep crater with up to a 40 degrees slope. Conditions in the
challenge were temperature -2 degrees Celsius, hard wind
and total darkness (without ambient light). Our robot was
third in the competition and won world-wide publicity in
newspapers, and on radio and TV.
Mörri platform performing in European Space Agency's Lunar Robot Challenge in Teide, Tenerife.
We will continue to strengthen our long term research
and researcher training. We will also continuously seek
opportunities for the exploitation of our research results by
collaborating with partners from industry and other
research institutions in national and international research
programs and projects. The group is a founding member of the
European Robotic Network of Excellence (EURON). The
group is a contract member of EURON II which was
approved for the EU's FP6 as a Network of Excellence.
We will strengthen our international research
co-operation. Within the last years, the group has created
collaboration projects with Japanese researchers. Several researchers
have visited Waseda University's Distributed Computing
Laboratory (DCL) to study ubiquitous computing paradigms.
The collaboration has given rise to results on sentient
(recognizing the user of an artefact), as well as activity
recognition and the corresponding architectural and data
collection issues. With the University of Tianjin, China we have a
joint project in which methods and a system will be
developed for vision-based navigation of Autonomous Ground
Vehicles, which utilize an omni-directional camera system
as the vision sensor. The aim is to provide a robust
platform that can be utilized in both indoor and outdoor AGV
(Autonomous Ground Vehicles) applications. This
co-operation will continue.
In the USA, we will co-operate with the
Human-Computer Interaction Institute in Carnegie Mellon University. A
doctoral student from ISG will make a one year research
visit to the institute and co-operate with assistant professor
Anind D. Key. The research will be on human modelling in
the area of human machine interaction.
A new co-operation agreement has been sealed during
year 2008 with IDIAP research in Switzerland. A post
doctoral researcher from ISG will make a one year research
visit starting March 2009. Shorter research visits to
European partners of EC funded projects are also planned.
professors & doctors 8 graduate students 27 others 42 total 77 person years 55 Source EUR Ministry of Education 282 000 Tekes 225 000 other domestic public 42 000 domestic private 154 000 international 532 000 total 1 235 000
Scientific Progress
Research on Prototyping: from a Smart
Environment towards Remote Distributed Intelligence
Research on Mobile Robotics
Research on Context-Aware Services
Research on Data Mining
Research on Software Security
Exploitation of Results
Future Goals
Personnel
External Funding
Selected Publications
Askola K, Puuperä R, Pietikäinen P, Eronen J, Laakso M, Halunen K & Röning J (2008) Vulnerability dependencies in antivirus software. Second International Conference on Emerging Security Information, Systems and Technologies (SECURWARE '08), Cap Esterel, France, 273-278.
Fujinami K & Riekki J (2008) A case study on an ambient display as a persuasive medium for exercise awareness. Lecture Notes in Computer Science: Persuasive Technology, Springer, 5033: 266-269.
Halunen K, Rikula P & Röning J (2008) On the security of VSH in password schemes. Third International Conference on Availability, Reliability and Security (ARES 2008), Barcelona, Spain, 828-833.
Juutilainen I & Röning J (2008) Modelling conditional variance function in industrial data: A case study. Statistical Methodology, 5(6): 564-575.
Kemppainen A, Mäkelä T, Haverinen J & Röning J (2008) An experimental environment for optimal Spatial Sampling in a Multi-Robot System. Intelligent Autonomous Systems 10 (IAS-10), Baden Baden, Germany, 54-63.
Koivikko M, Perkiömäki J, Karsikas M, Salmela P, Tapanainen J, Ruokonen A, Seppänen T & Huikuri H (2008) Effects of controlled hypoglycemia on cardiac repolarization in type I diabetes. Diabetologia, 51: 426-35.
Kortelainen J, Koskinen M, Mustola S & Seppänen T (2008) Remifentanil modifies the relation of electroencephalographic spectral changes and clinical end points in propofol anesthesia. Anesthesiology, 109: 198-205.
Kortelainen J, Koskinen M, Mustola S & Seppänen T (2008) Time-frequency properties of electroencephalogram during induction of anesthesia. Neuroscience Letters, 446: 70-4.
Koskimäki H, Juutilainen I, Laurinen P & Röning J (2008) Detection of Correct Moment to Model Update. Lecture Notes in Electrical Engineering: Informatics in Control, Automation and Robotics, Springer Berlin Heidelberg, 24: 87-94.
Peltola M, Tulppo M, Kiviniemi A, Hautala A, Seppänen T, Barthel P, Bauer A, Schmidt G, Huikuri H & Mäkikallio T (2008) Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction. Annals of Medicine, 40: 376-382.
Pietikäinen P, Viide J & Röning J (2008) Exploiting Causality and Communication Patterns in Network Data Analysis. 16th IEEE Workshop on Local and Metropolitan Area Networks (LANMAN 2008), Cluj-Napoca, Transylvania, Romania, 114-119.
Riekki J, Sánchez I & Pyykkönen M (2008) Universal Remote Control for the Smart World. Lecture Notes in Computer Science: Ubiquitous Intelligence and Computing, Springer, 5061: 563-577.
Röning J, Haverinen J, Kemppainen A, Mörsäri H & Vallivaara I (2008) Smart Systems for Distributed Sensing. Proceedings of 11th Biennial Baltic Electronics Conference (BEC2008), Tallinn, Estonia, 21-30.
Schaberreiter T, Wieser C, Sánchez I, Riekki J & Röning J (2008) An Enumeration of Rfid Related Threats. Proc. The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM’08), Valencia, Spain, 381-389.
Seydou F, Duraiswami R & Seppänen T (2008) Numerical solution of electromagnetic scattering by multiple cylinders. ACES Journal, 23.
Siirtola P, Laurinen P & Röning J (2008) A Weighted Distance Measure for Calculating the Similarity of Sparsely Distributed Trajectories. Seventh International Conference on Machine Learning and Applications, San Diego, USA, 802-807.
Suutala J & Röning J (2008) Methods for Person Identification on a Pressure-sensitive Floor: Experiments with Multiple Classifiers and Reject Option. Information Fusion Journal, Special Issue on Applications of Ensemble Methods 9(1): 21-40.
Tamminen S, Juutilainen I & Röning J (2008) Product Design Model for Impact Toughness Estimation in Steel Plate Manufacturing. The International Joint Conference on Neural Networks (IJCNN 2008), Hong Kong, 990-993.
Tiinanen S, Tulppo M & Seppänen T (2008) Reducing the effect of respiration in baroreflex sensitivity estimation with adaptive filtering. IEEE Transactions on Biomedical Engineering 55: 51-9.
Vallius T & Röning J (2008) Low Cost Arbitration Method for Arbitrarily Scalable Multiprocessor Systems. 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008), 119-124.
Noponen K, Kortelainen K & Seppänen T (2008) Invariant trajectory classification of dynamical systems with a case study on ECG pattern recognition. Pattern Recognition. In print.
Pirttikangas S, Fujinami K & Hosio S (2008) Experiences on data collection tools for wearable and ubiquitous computing. Int. Symposium on Applications and Internet (SAINT2008), Workshop on SensorWebs, Databases and Mining in Networked Sensing Systems (SWDMNSS 2008), IEEE, July 28, Turku, Finland, 149-152.