Ambient Intelligence for Better Buildings

Abstract: The tutorial will cover lessons learned from a long-term study of the uses of sensor networks in buildings. The goal of these networks is to observe the people, recover the patterns of behavior and then find ways to leverage those patterns to improve building efficiency, safety, security, and utility. Along the way we've learned some things about the sensing modalities, pattern recognition, the business of building management, and the privacy implications of pervasive sensor networks. These topics will be discussed in a practical way, while embedding the work in the context of the research literature.

Speaker: Dr. Christopher R. Wren is a Research Scientist at the Mitsubishi Electric Research Laboratories in Cambridge, MA, USA. His work on perception is targeted at improving human-system interactions. His current research focus centers on the perceptual problems associated with sensor networks, specifically perceiving and modeling the behavior of populations of people in buildings. Prior to joining MERL, he was a member of the Vision and Modeling Group at the MIT Media Laboratory where he developed real-time vision systems to understand individual human behavior. Dr. Wren has also worked in interface, graphics, haptics and simulation.

Tutorial on Computational Intelligence for Sensor Networks Applications

Abstract: Computational intelligence is the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments. These mechanisms include paradigms that exhibit the ability to learn or adapt to new situations, generalize, abstract, discover and associate. CI has found extensive practical applications in many areas including - but not restricted to - robotics, intelligent control, cybernetics and sensor networks.

A sensor network is a network of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. Though the development of sensor networks was initially stimulated by military applications such as battlefield surveillance, wireless sensor networks are now used in numerous civilian applications like environmental monitoring, habitat monitoring, prediction and detection of natural calamities, medical monitoring and structural health monitoring.

Advances in sensor technology and computer networks have enabled sensor networks to evolve from small clusters of large sensors to large swarms of miniature sensors, from wired communications to wireless communications, and from static network topology to dynamic topology. In spite of these technological advances, sensor networks still face the challenges of communication and processing of large amount of data in resource constrained environments. In last decade, paradigms of CI have been widely used as attractive tools to address the challenges in sensor networks.

This tutorial will introduce the major paradigms of computational intelligence and review recently reported CI applications in sensor networks. The specific CI paradigms and applications to be covered include artificial neural networks, swarm intelligence, fuzzy logic, evolutionary computing, artificial immune systems, optimal sensor placement, self coordination, optimal routing, source localization, information fusion, and optimal power usage.

Speaker: Ganesh Kumar Venayagamoorthy, Senior Member, IEEE and Raghavendra Kulkarni, Senior Member, IEEE, Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri-Rolla, MO 65409, USA

Intelligent sensor data acquisition with mobile handheld devices

This tutorial has been cancelled due to unavoidable circumstances. We apologize for any inconvenience. In place of the tutorial originally planned we will be running a Working Group Meeting / Workshop on Sensors for the Great Barrier Reef. Details are as follows:

Sensors for the Great Barrier Reef - Workshop.

Hosted by ISSNIP 2007
Monday, December 3, 2007
Langham Hotel, Melbourne

The Sensors for the Great Barrier Reef - Workshop will be a working group meeting with the aim of identifying the ongoing research and implementation challenges faced by sensor network deployments in the Great Barrier Reef. In addition, it will illustrate the opportunities for researchers interested in this area to be able to evaluate the sensor networks developments in the corresponding deployments. Researchers, especially those from the ISSNIP network, with some background in embedded hardware/software development, and who are looking for opportunities to implement/test their algorithms in a challenging environment, are strongly encouraged to participate.

Speakers to include:
- Ron Johnstone (University of Queensland)
- Ian Atkinson (James Cook University)
- Scott Bainbridge (Australian Institute of Marine Science)
- Stuart Kininmonth (Australian Institute of Marine Science)
- Yee Wei Law (The University of Melbourne)
- Sutharshan Rajasegarar (The University of Melbourne)