pattern recognition for wireless sensor networks
DESCRIPTION
Mohamed Baqer [email protected]. Pattern Recognition for Wireless Sensor Networks. 24 May 2007. Outline. Sensor Networks Energy Conservation Patterns and Sensor Networks Application So What’s the Big Deal? Challenges of Event Recognition in Sensor Networks - PowerPoint PPT PresentationTRANSCRIPT
2M. Baqer [email protected]
Outline • Sensor Networks• Energy Conservation• Patterns and Sensor Networks• Application• So What’s the Big Deal? • Challenges of Event Recognition in Sensor Networks• Event Recognition for Sensor Networks• Voting Graph Neuron• VGN Model• Voting and Consensus• Sleeping Mode• Example• SGSIA• Summary
3M. Baqer [email protected]
Sensor Networks
• Random vs. deterministic deployment• Long term deployment• Dynamic infrastructure• Unattended operations• Scale
4M. Baqer [email protected]
Energy Conservation
• Scheduling-based– Operation mode (transmitting, receiving,
idle, sleeping)
• In-network Processing-based– Aggregation
– Compression
– Beamforming
– CSIP
5M. Baqer [email protected]
Patterns and Sensor Networks
• Spatio-temporal event patterns• Pattern collection
– continuously
– periodically
– Even-driven
– User-driven
– hybrid
6M. Baqer [email protected]
Application: Structural Health Monitoring
• SHM replace visual inspection
• Applied for– Predict– Detect– monitor
structures for damages
7M. Baqer [email protected]
So, What’s the Big Deal?
• Can’t centralised servers (base station / sink node) perform pattern recognition for sensor networks?– Geographically dispersed sensory data
– Require global information
– Communication overhead
– Offline detection
8M. Baqer [email protected]
Challenges of Event Recognition in Sensor Networks
• Global vs. local• Constraint resources• Dynamic infrastructure• Energy efficiency• Scalable
9M. Baqer [email protected]
Event Recognition for Sensor Networks
• Template matching• Distributed artificial intelligence• Cooperative distributed problem solving
11M. Baqer [email protected]
VGN algorithm
• Votes vectors:– Local match
• Use:– Local processing, information exchange and
decision fusion
• Consensus– Cooperatively negotiating by casting votes
– Cast and rebuild vote vectors
12M. Baqer [email protected]
Sleep Mode
• Committee members enter into sleep mode to conserve their energy
• Who may go into the sleep mode?– Committee members that already cast their vote
– Committee members with identical votes
• When do identical vote vectors get created?– Initialisation stage
– Negotiation stage
13M. Baqer [email protected]
Example
Input sensory pattern Committee negotiation process
Colour map of the negotiation process
14M. Baqer [email protected]
Comparison results of the difference in the pattern matching performance for committee storing random patterns and alphabet character patterns
15M. Baqer [email protected]
SGSIA
• In-network Data Processing for Secure Grid-Sensor Integration Architecture
• Provide timely and accurate responses to data acquisition requests intended for WSNs
• Data processing at the sensor nodes to filter raw sensory data
• Optimal and selective forwarding of grid-generated queries to the appropriate sensor networks.
• Grid proxy: interface, QoS, cashing
• Gateway (base station): managing, fuse, translate
17M. Baqer [email protected]
Summary
• Ambient intelligence• Decentralised in-network pattern
recognition• Scalability• Adaptability
