Paper Info
Title
Decentralized smart sensor scheduling for multiple target tracking for border surveillance
Abstract
Border surveillance requires regular patrolling to prevent intruders from crossing across, emphasizing the need for an automated network of sensing devices that is capable of detecting and estimating multiple moving targets. This paper proposes a fusion-driven decentralized sensor scheduling scheme that enables dynamic space-time clustering around multiple moving targets for energy-efficient track estimation. Each sensor node runs a Probabilistic Finite State Automata (PFSA) that controls the sensing and communication devices in an energy-efficient manner. This decentralized scheduling scheme is validated and compared with traditional scheduling schemes. The results show that the proposed scheme conserves energy while maintaining accurate track estimation.
Year
DOI
Venue
2015
10.1109/ICRA.2015.7139649
IEEE International Conference on Robotics and Automation
Keywords
Field
DocType
finite state machines,intelligent sensors,motion estimation,object detection,pattern clustering,probability,scheduling,sensor fusion,surveillance,target tracking,wireless sensor networks,PFSA,automated network,border surveillance,dynamic space-time clustering,energy-efficient track estimation,fusion-driven decentralized smart sensor scheduling scheme,multiple moving target detection,multiple moving target estimation,multiple target tracking,probabilistic finite state automata,sensing devices,wireless sensor network
Sensor node,Scheduling (computing),Computer science,Patrolling,Real-time computing,Dynamic priority scheduling,Cluster analysis,Processor scheduling,Probabilistic finite state automata,Energy consumption,Distributed computing
Conference
Volume
Issue
ISSN
2015
1
1050-4729
Citations 
PageRank 
References 
1
0.36
13
Authors
3
Name
Order
Citations
PageRank
James Hare121.38
Shalabh Gupta231.44
James Wilson372.87