iSENSE
Communications and Information Technology Ontario (CITO)
INCO Mines
Co-investigator: Prof. Dimitris Makrakis
Description of the Research
Introduction and Overview.
The rise of Internet technologies and standards in the recent past has caused a very rapid convergence of computing and communications technologies. IBM Global Services make the following observations [1; p.29] about the so far four major movements in the computing industry: the first era was the central computing, or mainframe, era that span the years 1950 to 1980. The second was the PC era, which began in the 1980s. The third was the network era, which really started in the 1990s with the rapid growth on the Internet and computer networking. The network era of computing promises dramatic changes in the nature of work and commerce, and in the structure of the industry. While this era is still unfolding, a fourth era is foreseen emerging, once all technologies of the networked computing era have stabilized and have been integrated into the majority of businesses and households. This will be the era of Pervasive Computing where the emphasis shifts from information and communication technologies to information and communication per se [1; p.30]. Computers will become pervasive technology, that is, a technology more noticeable by its absence than its presence, [2].
Pervasive computing will give us tools to manage information easily. Information is the new currency of the global economy. We increasingly rely on the electronic creation, storage, and transmittal of personal, financial, and other confidential information, and demand the highest security for all these transactions. We require complete access to time-sensitive data, regardless of physical location. We expect devices -- personal digital assistants, mobile phones, office PCs, sensors, appliances and home entertainment systems -- to access that information and work together in one seamless, integrated system. Pervasive computing can help us manage information quickly, efficiently, and effortlessly.
Research reports on pervasive computing is only now emerging in refereed publications, at least to our knowledge. IBM is a major industrial player in pervasive computing [9, 10] and they have recently announced strategic alliances with many companies, among which the Ottawa-based QNX Software Systems Ltd. A major project (Oxygen) has recently (April 1999) been initiated by the MIT Laboratory for Computer Science [4]. Oxygen is an integrated collection of eight new technologies: handheld PDAs, wall and trunk computers, a novel net, speech understanding, knowledge access, collaboration, automation and customization. Stanford University [3] is another early contributor.
The first mass-produced pervasive computing devices are starting to appear. The Clarion AutoPC [5] provides an efficient, reliable and secure integrated communications, computing, navigation, car control and entertainment system. The NCR Microwave Oven/Home Banking Terminal [6] and the Electrolux Internet Connected Screen Fridge [7], allow effortless home management. A good example scenario is given in [3]. Opening the fridge to take out a soda, you notice that there is only one left. The "smart" fridge has recorded that and adds an action item on your shopping list. The next day, as you drive home from work, the GPS-enabled AutoPC in your car, previously informed by your fridge that purchases need to be made, signals that you are near a supermarket. As you cruise the isles of the supermarket, wearing your augmented-reality goggles and your wearable computer [8], a soda supply triggers an object recognition program and an alarm reminds you to buy soda. The same of course could be done by your pocket Personal Digital Assistant (PDA) sensing the presence of the soda supply.
Another pervasive computing example was given by IBM Chairman Gerstner in [9]: "Think about driving down the autobahn. Your intelligent car develops an engine problem, but instead of flashing you a warning light it sends a message directly to the manufacturer over a wireless connection to the network. The manufacturer's systems diagnose the problem and transmit a fix back to the electronics complex in your car. In fact, that corrective fix is transmitted to all models everywhere in the world, without ever having to notify the owners. .... Instant information on performance is captured and sent immediately into product development and manufacturing. Continuous feedback loop, continuous improvement, resulting in better cars. Good for consumers".
Electric motors are an example of pervasive technology [2]. The average US home contains two dozen or more electric motors. A multitude of sensors are gathering the information needed to control them. As all these are buried inside many appliances (vacuum cleaners, microwave ovens, refrigerators, VCRs, etc.) we have difficulty identifying them and we don't even care where and how many they are. In the future, the same will be true with computers, most of which will be hidden in information appliances. These new appliances are "smart devices" embedded with microprocessors that allow users to plug into intelligent networks and gain direct, simple, and secure access to both relevant information and services. These devices are as simple to use as calculators, telephones or kitchen toasters. Pervasive Computing envisions the "networked home" where domestic devices can interact seamlessly with each other and with in-home and external networks. Using the existing home infrastructure based on open industry standards, a person will be able to integrate the home network with external networks to easily manage home devices, both locally and remotely.
Digital and more recently computer-based instrumentation and measurement technologies have evolved over the last 30 years in order to provide an interface to the physical world for many computer based industrial control applications, [11], [12], [13], [14], [19]. The advent of the pervasive computing provides new incentives for the development of even more efficient and versatile sensing technologies. New sensors are needed to measure a greater diversity of parameters in order to provide a wider, more dynamic and more information-rich window on the environment.
Recent progress in computer and VLSI technologies allow the use of complex signal and image processing, system identification, modelling, control, and AI algorithms, as well as user friendly virtual environments for the development of an ever growing diversity of real-time intelligent sensing applications ranging from Computer Integrated Manufacturing (CIM) to smart homes and offices. These new developments point to the emergence of a new type of intelligent control based on a multisensory perception of the state of the controlled process and its environment [15], [16]. These intelligent model-based adaptive controllers provide an intelligent connection of the perception to action to achieve specified goals in complex changing environmental situations. World models, built and maintained from information gathered by a multitude of sensors, provide a common abstract representation of the state of the environment. At the perception level, the world model is analyzed to infer relationships between different objects and assess the consequences of the controller's actions.
The perception capability is an AI-oriented active investigatory window providing global information that reduces the uncertainties about the physical state of the controlled process and its environment [20]. The only a priori defined constraint in this case is what parameters are to be measured without necessarily knowing where or when or even if they will occur. The question of how multiple sensor data are integrated in world models adds a new dimension to what can be called the perception paradigm.
More human-like intelligence based on neural networks, fuzzy logic, and expert systems will be incorporated on a wider scale in the new generation of instruments and measurement methods. Virtual instruments will evolve to become even more user-friendly by providing interactive sensor-based virtual environments for telepresence operations, where human operators will be integrated in hybrid man-machine control loops as ultimate strategic-level decision makers [17], [18].
As their perception ability grows thanks to intelligent sensing the information appliances are evolving into sensor-based intelligent appliances representing the next evolutionary stage for the pervasive computing paradigm. These intelligent appliances will behave like pervasive intelligent autonomous robotic agents providing a seamless intelligent connection of the perception to action, [15].
While the smart networked home is a very good showcase for information
appliances, the intelligent sensing agents and sensor-based appliances
will allow the pervasive technology idea to spread to other areas of human
activity as for instance the mining and manufacturing industries, security
industry, transportation, training and health etc. It will not be
exaggerate to claim that this technology, when integrated in the emerging
global information infrastructure, will have a profound impact on our personal
and professional activities, and open business opportunities, of similar
or even higher scale to what we are experiencing presently with Internet.
Description of the research in detail
Early digital and computer-based instrumentation architectures and communications standards as HP-IB (IEEE 488) represented embryonic smart sensing solutions supporting the first generation of computer based industrial applications. Microprocessor controlled sensors and virtual instrumentation integra tion environments such as LabView together with the wireless and internet communications have then allowed to develop a larger variety of embedded industrial applications. The advent of pervasive computing marks an urgent need for a new generation of intelligent sensing agents and sensor-based appliances and related resource management environments for a broader area of applications involving loosely coupled, event-driven, heterogeneous intelligent sensing agents and appliances.
1. Development of intelligent sensing agents and sensor-based intelligent
appliances for pervasive computing applications in heterogeneous environments.
Intelligent sensing agents will be developed as autonomous agents carrying
out task-directed active investigation of specific environment parameters.
Reliable communication modalities will allow them to cooperate in order
to monitor the multi-parameter state of large systems. Intelligent sensing
functions will also be embedded together with computing and actuation functions
in intelligent appliances for pervasive computing applications.
Model based sensor architectures for both propriceptors, i.e., sensors
monitoring the internal state of an information appliance, and exteroceptors,
i.e., sensors monitoring the state of the environment outside the information
appliance, using sensor- and world-models will provide superior modularity,
interchangeability (plug and play) and transparence allowing for easier
sensor fusion and knowledge extraction. Sensor models will be used to describe
how sensors observe parametrically represented objects and Bayesian probability
will be used to represent sensor models. Statistical as well as fuzzy and
neural network methods will be studied for sensor fusion.
Intelligent task-directed information gathering features will be studied
to allow for a more elastic and efficient use of the inherently limited
sensing and processing capabilities of each agent. Each task a sensing
agent has to carry out determines the nature and the level of the information
that is actually needed. Sensing agents should be able of selective environment
perception that focuses on parameters important for the specific task at
hand and avoid wasting effort to process irrelevant data. A task-specific
decision making process will guide the incremental refinement of the environment
model.
Each intelligent sensor will be developed as an intelligent agent able
to learn/adapt, able to deal with multiple redundant communication carriers
(intranet, internet, power lines, wireless, infrared,..).
2. Development of versatile man-machine sensing interfaces
allowing messaging for real-time control and/or communication between sensors
and human operators/users.
Research in the field of computer-human interfaces (CHI) has been extensive.
As the era of pervasive computing commences, portable wireless PDAs or
wearable computers will be widely used. New CHI paradigms (e.g., retinal
projection) and designs are thus called for and this research will be addressing
them. Design of versatile man-machine interfaces allowing messaging for
real-time control and/or communication between sensors and human operators/users
will be investigated. Voice recognition and synthesis for iSENSE PDAs will
be researched. Our recent experience in using Distributed Virtual Environments
in CHI design, with applications to e-commerce and industrial tele-training,
will be an asset in this research. An example application will be telecontrol
in a hazardous mining environment.
3. Design of temporal synchronization protocols among sensors,
actuators and/or human operators.
Multimedia synchronization typically refers to the temporal relations
among media such as video, audio, graphics, images, text, etc, produced
during the authoring of a multimedia document. Temporal asynchronies are
due to network and devices delay, delay variation, buffer sizes,
available bandwidth. This research will extend recent results in media
synchronization protocols [23, 27], designed for compensation of media
asynchronies of the order of 100 msec or higher, to much stricter temporal
constraints of the order of a few msec or microseconds, pertinent to sensors
and actuators relationships. An example in computer-integrated manufacturing
is the actuation of a robot-controlled welding operation on an assembly
line upon a sensor command.
4. Design of networking technologies for the support of pervasive
intelligent sensing agents and appliances.
As a very large number of devices will be serviced through the
wireless and wire-line global networks infrastructure, existing technologies
will be rendered inefficient; new solutions have to be invented. The nature
of pervasive computing and services devices require that the developed
architectures should distributed rather than centralized. Our work will
take into account both the developing PAN (Personal Area Networks) (IEEE
802.15), media access control and existing Local and Wide Area Network
Standards (e.g. IEEE 802.11), Internet Protocols (Mobile IP, IPv6, RTP/RTCP,
RSVP, XTP etc.). However, we expect that the size and complexity of the
problem would require the development of new technologies and standards.
The objective of our research will be to develop Distributed Networks Architectures
(DNA) suitable for the support of pervasive computing at a large scale.
Our work will address wired and wireless networking issues and development
of cost-effective solutions for environments where deployment of advanced
networking infrastructure could be unjustifiably costly. Our solutions
will address both Internet and Intranet architectures. The following
activities will be part of our research:
· Accurate modeling of tele-traffic produced by such devices
and assessment of network impairments on the performance
Accurate knowledge of the new traffic dynamics is essential, since
successful design of networking technologies and applications requires
accurate knowledge of tele-traffic behaviour.
· Development of “service” admission control and connection
establishment policies, as well as resource allocation and resource adaptation
algorithms for the support of pervasive devices.
Pervasive devices will require the service of a highly inhomogeneous
global network. Our work will be focused around the Internet protocol
suite (Mobile IP and Cellular IP, IPv6, RTP/RTCP, RSVP) and address deployment
over heterogeneous networks. It will also address the realities of
distributed network architectures and the need for balanced loading of
the network based resources, while the QoS of the applications/services
is safeguarded.
· Development of Quality of Service capable, error-resilient
and resource allocation-efficient multiple access protocols for the efficient
transportation of sensor traffic.
The bandwidth and resource limitations of the wireless medium require
that that information content is “compressed” as much as possible, in order
to “consume” the least amount of resource possible. However, such
low redundancy makes the information vulnerable, especially in an error-prone
environment such as wireless channels and networks. In our work, the resource
mapping policies between the wired and wireless network and the protocol
interoperability issues will be addressed.
· Development of “intelligent networking” infrastructure and
definition of suitable architectures of distributed nature.
The proposed solutions will be capable of: a) servicing the processing
requirements of pervasive devices, b) provide them with full mobility support
and c) guarantee their operation in a seamless fashion. This
requires extension of the “Intelligent Networking” concepts to the Internet
and Wireless Internet.
· Development of cost-effective network solutions for environments
where there is no advanced networking infrastructure deployment.
We plan to develop suitable technologies for establishing inexpensive
LANs for pervasive computing and intelligent sensing applications. Various
avenues, such as use of the power line network will be investigated.
5. Agent-based framework allowing management of heterogeneous
functions for a large diversity of distributed intelligent sensors and
pervasive computing appliances.
Pervasive computing environments involve both human-machine and machine-machine
interaction and cooperation paradigms. The research will concentrate on
machine-machine aspects. We are all familiar with human-to-human communication
and cooperation, which require a common language and an underlying system
of shared knowledge and common values. In order to achieve a similar
degree of machine-machine interaction and cooperation, we will develop
a framework allowing management of heterogeneous functions and knowledge
for a large diversity of pervasive computing devices. This framework will
address functionality at a level of abstraction higher than that of the
classical communication network protocols, and even than that of coordination
frameworks such as ODP (Open Distributed Processing) and CORBA (Common
Object Request Broker Architecture), which provide mainly distribution
transparency. The heterogeneous pervasive computing devices cannot realistically
be expected to have a common language and understanding of each other's
functions. Accordingly, the proposed functionality management framework
will investigate integration mechanisms allowing different domain-specific
devices to communicate, understand each other and collaborate toward common
goals. In order to provide a flexible extensible open framework,
we will develop methods by which different devices will exchange the grammars
describing their domain-specific languages and learn to understand each
other. This way, the devices will be able to advertise their own functions,
search and discover providers of required services, and express their needs
in a collaborative environment.
6. Case study:
Environment monitoring, telesensing and remote-controlled robots are
currently developed for hazardous operating environments: fire, explosive,
chemical, nuclear, mine fields, underwater, as well as space. As the complexity
of tasks increase and the need for real time reactive behaviour becomes
critical, the robots will require to be capable of teleautonomous behavior.
We will design a pervasive computing system using intelligent sensing
agents and sensor-based appliances, i.e. intelligent sensing
robotic agents, for multi-parameter monitoring and real-time
telecontrol in a hazardous mining environment (INCO). This pervasive
computing environment will be supported by a real-time resource management
system using the QNX real-time operating system
Essential for the control of the robotic agents is an embedded perception
system able to timely and correctly assess the state of the robot's physical
environment. The use of multiple sensors is beneficial in improving
the accuracy, the cost and robustness of the perception process.
Many of these applications are impossible to fully automate and remote
human operator expertise is still needed to carry out tasks requiring a
higher level of intelligence. A proper control of these remote operations
cannot be accomplished without some telepresence capability allowing the
human teleoperator to experience the feeling that he/she is in the remote
environment.
The specific objectives are: (i) the development of intelligent exteroceptor
sensing agents and teleautonomous robotic agents, (ii) the design of a
model-based multi-sensor fusion system able to integrate a variety of sensors
that cover all four phases in the environment perception process: far away,
near to, touching, and manipulation, (iii) the study of new task-directed
sensor fusion and learning methods for an active perception which will
allow the robot to gather information by interaction with the environment
(iv) to provide human oriented geometric- and force-domain telepresence
feedback for teleoperation, (iv) design of a redundant multi-carrier communication
system for the sensing and robotic agents.
Machine learning techniques will be studied for the real-time reactive
behavior of the sensing and robotic agents. A variety of reinforcement
learning paradigms using learning classifier, neural networks, fuzzy logic,
and Q-learning, as well as the evolutionary learning paradigm will be studied
to implement basic reactive behaviors that accomplish simple tasks. In
order to find more efficient solutions to the complex tasks we will study
the combination of the intrinsic reactive-behavior with higher-order world
model representations of the environment.
In terms of networking technology, the activities described earlier
will be pursued. Prototypes will be developed and integrated in the test-beds
at U of O and at INCO’s research facilities. INCO will be making
available to us their research facilities in Copper Cliff, Ontario for
testing our developments. We will have access to the underground
wireless and wired underground networks and the high speed network that
is used to transport information between their research facility and the
headquarters.
General references:
1. "Assessing the Strategic Value of Information Technology", Research
Report, The Economist Intelligence Unit Ltd and IBM Global Services, N.Y.,
1999
2. J. Birnbaum, "Pervasive Information Systems", Communications of
the ACM, Vol. 40, No.2, Feb. 1997, pp. 40-41
3. A.C. Huang, B. Ling, S. Ponnekanti, and A. Fox. "Pervasive Computing:
What Is It Good For?" Workshop on Mobile Data Management (MobiDE)
in conjunction with ACM MobiCom 99 (to appear).
4. M.L.Dertouzos, "The Future of Computing", Scientific American, 52,
Aug. 1999, pp.52-55; also "MIT Oxygen Project" http://www.lcs.mit.edu/anniv/press/oxygen040799
5. Clarion Corp., "Auto PC ," http://www.autopc.com/walkthrough/communication/,
1999
6. NCR Corp., "NCR Microwave Oven / Home Banking," http://www.wired.com/news/news/technology/story/14949.html,
1999
7. Electrolux Inc., "Electrolux screen Fridge", http://www.wired.com/news/news/email/explode-infobeat/technology/story/%17894.html,
1999
8. S. Mann, "Wearable Computing; A first Step Toward Personal
Imaging", IEEE Computer, 30 (2), Feb. 1997
9. L. Gerstner, "Pervasive Computing" , Keynote -CeBIT 98,
http://195.27.241.3/news/news1/ns-3975.html
10. IBM, "What is Pervasive Computing", http://www-3.ibm.com/pvc/pervasive.html
11. M. Hardwick, D.L. Spooner, T. Rando, K.C. Morris, "Data Protocols
for the Industrial Virtual Enterprise," IEEE Internet Computing, vol. 1,
no. 1, Jan-Feb. 1997, pp. 20-29.
12. R. Itschner, C. Pommerell, M. Rutishausser, "Glass: Remote Monitoring
of Embedded Systems in Power Engineering," IEEE Internet Computing, vol.
2, no. 3, May-June. 1998, pp. 46-52.
13. P. Dabke, "Enterprise Integration via CORBA-Based Information Agents",
IEEE Internet Computing, vol. 3, no. 5, Sept-Oct. 1999, pp. 49-57.
14. C.M. Pancerella, N.M. Berry, "Adding Intelligent Agents to Existing
EI Frameworks," IEEE Internet Computing, vol. 3, no. 5, Sept-Oct. 1999,
pp. 60-61.
15. A. Brooks, L.A. Stein, "Building Brains for Bodies", Autonomous
Robots, Vol. 1, No.1, pp. 7-25, 1994.
16. B.V. Dasarathy, "Sensor Fusion Potential Exploitation – Innovative
Architectures and Illustrative Applications," Proc. IEEE, Vol. 85, No.
1, pp. 24-38, Jan. 1997.
17. R.W. Picard, "Human-Computer Coupling," Proc. IEEE, Vol. 86, No.
8, pp. 1803-1807, Aug. 1998.
18. S. Mann, "Humanistic Computing: "WearComp" as a New Framework and
Application for Intelligent Signal Processing," Proc. IEEE, Vol. 86, No.
11, pp. 2123-2151, Nov. 1998.
19. R. Sasdelli, C. Muscas, L. Peretto, "A VI-Based Measurement System
for Sharing the Customer and Supply Responsibility for Harmonic Distortion,"
IEEE Trans. Instrum. Meas., Vol. 49, No. 5, pp. 1335-1340, Oct. 1998.
20. K. Kariya, S. Takayama, H. Kochi “Laboratory Model for Thinking
of Measurement Science,” in Instrumentation and Measurement Technology
and Applications, (E.M. Petriu – Edit.), pp. 13-18, IEEE Press, New
York, 1998.
21. A.A. Platonov, J. Szabatin “Analog-Digital System for Adaptive
Measurements and Parameter Estimation of Noisy Processes,” in Instrumentation
and Measurement Technology and Applications, (E.M. Petriu – Edit.), pp.
259-268, IEEE Press, New York, 1998.
22. E. Steenput, Y. Rolain “Auto-Consistent Mathematical Environment
for Measurement Software Development,” in Instrumentation and Measurement
Technology and Applications, (E.M. Petriu – Edit.), pp.280-285, IEEE
Press, New York, 1998.
MILESTONES
Dec. 2000 Development of first Intelligent Sensor Architecture completed; Assessment of temporal synchronization requirements in iSENSE competed; Study of existing PDA interfaces and capabilities for pervasive computing completed; Preliminary design of wireless or integrated networking architecture completed.
Mar. 2001 Development of first new synchronization protocol completed; First man-machine interface, using voice recognition, completed; Tele-traffic modeling of interconnected devices completed; new wireless protocols study completed; Case study for mining application initiated.
Dec. 2001 Intelligent Network activities initiated; research on presence, position tracking sensors, interfaces, retina projections initiated; Design of new synchronization protocol for large distributed environments completed.
Mar. 2002 Implementation and performance evaluation of distributed synchronization
protocol completed; Implementation and evaluation of new CHI completed;
Intelligent Networking research completed; case study completed and final
demo of complete iSENSE prototype test bed.