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Networks for Security Applications. Defense Security Innovation Quebec City, Nov. 16, 2007 Prof. Howard M. Schwartz. Presentation Outline. Who we are. Research Centre in Technology Innovation (RCTI). Networks for Security Applications. Wireless Sensor Networks.
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Networks for Security Applications Defense Security Innovation Quebec City, Nov. 16, 2007 Prof. Howard M. Schwartz
Presentation Outline • Who we are. • Research Centre in Technology Innovation (RCTI). • Networks for Security Applications. • Wireless Sensor Networks. • Sensors, Circuits and Devices for Security. • Networks and Swarms of Autonomous Vehicles (UAVs). • Network Intelligence and evolution • Simulation • Conclusion
Who is RCTI? • 31 Professors at all levels. • From 6 Departments and 3 Faculties. • Systems and Computer Eng., Electronics, Mechanical Eng., Computer Science, Information Technology and Business. • Advance research and scholarly activity in electrical and systems engineering, computing science, and the development and commercialization of new products • Link R&D carried out by Carleton faculty and graduate students with companies. • Be a valuable source of talent, knowledge, prototypes, and technology to innovative companies. • Member of Technopôle Security and Defense
Networks of things Networks that perceive, understand and take action for security applications. - Border security - Industrial control and security - Power grid control and security - Transportation systems - Telephone, internet communication systems
Example of a Complex Network (Scenario developed by RUNES project: http://www.ist-runes.org/)
Wireless Ad Hoc Network • Air drop wireless sensors over region. The system establishes its communication topology. Low power, low cost devices that are easily augmented and replaced.
Research For Wireless Networks • Facilitate the collection of sensor data from a collection of resource-constrained sensor systems, connected wirelessly. How should the sensors talk to each other? • Support new applications and the re-tasking of wireless nodes. • Support easy integration of new sensors. • Efficient distribution of the information from the sensors to various interested parties (first responders, airport authorities, etc.). • Combine/fuse data derived from different sites. • Wireless mesh testbed, consisting of 14 custom-build mesh routers and a range of client devices (PDAs, laptops, etc.).
Cyber-infrastructure for Bridge Monitoring • Continuously monitoring bridges in the country is an important goal • Management of Bridge Infrastructure can save life and reduce maintenance cost • Monitoring of large number of bridges, managing and making information available at finger tips, automated health & condition assessments and management, maintenance and emergency response are various facets of this problem • Monitored data can be of various types: sensor data, video data, acoustic, visual inspection etc.
Research Directions in Sensors and Vehicles (The Things) • Biosensors and authentication. • Autonomous vehicles (Land, Air and Sea). • Video sensors (Cameras)and video understanding. • Super resolution enhancement.
Bio-sensors • The heart rate and breathing monitor.
Iris Retina Fingerprint Face Voice • Biometrics from biosensors provide some promising solutions to the authentication problems. Cardio-based Finger vein
Military tactical mobile ad hoc networks (MANETs) challenge security design. • As the front line of defence, authentication is the core requirements for integrity and confidentiality in networked centric warfare.
Research into Wireless Bio Sensors. • development and evaluation of biosensor wireless networking and management schemes that take into account wireless communication, power consumption and computational resource requirements, • development and evaluation of biometric-based user authentication and encryption for high security wireless communications,
Cooperative robots and intelligence • Robots have own control and navigation algorithms • Robots only know their position and others
Video Processing and Understanding Tracking of video objects
Intelligent Video Object Tracking Tracking, counting and timing of video objects.
Swarm Intelligence and Personality Evolution • Game Theory, Coalition formation. • Evolutionary Game Theory. • Learning (fuzzy, adaptive, genetic). • Personality Traits.
Simulation • A rich simulation environment for network development, operator training and visual display.
Conclusions • The Research Centre in Technology innovation is a unique grouping of 31 faculty and 100’s of students. The goal is to work closely with industry to bring new innovative ideas to market. • The research is focused on networks of sensors and devices. • Applications in Security and Defense. • Expertise and research in sensors, wireless systems, autonomous vehicles and computer networks. • Research into network intelligence, swarm intelligence and adaptive and learning systems. • Networks that perceive, understand and take action.