Spatio-Temporal Forest Fire Detection using a Distributed Hierarchical Graph Neuron within an Integrated Wireless Sensor Network-Grid Environment
Critical applications in the engineering and scientific area such as Structural Health Monitoring (SHM) and forest fire detection requires active detection mechanisms, which utilise current technology such as Wireless Sensor Network (WSN). Nevertheless, existing event detection applications implemen...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/5727/1/MUHAMAD.PDF http://www.civil-comp.com/conf/photop11.htm http://eprints.utp.edu.my/5727/ |
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| Summary: | Critical applications in the engineering and scientific area such as Structural Health Monitoring (SHM) and forest fire detection requires active detection mechanisms, which utilise current technology such as Wireless Sensor Network (WSN). Nevertheless, existing event detection applications implemented on WSN are far from achieving its fullest potential. In this paper, we propose a distributed intelligent event detection scheme known as Distributed Hierarchical Graph Neuron (DHGN) that performs pattern recognition on spatio-temporal sensory data within an integrated WSN-Grid environment. Fire detection data is analysed over a simulated WSN network. The results indicate that DHGN produces high recognition accuracy and is capable of performing spatio-temporal event tracking within specified locations and time instances. |
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