Energy-efficient Multiple Targets Tracking Using Target Kinematics in Wireless Sensor Networks Akond Ashfaque Ur Rahman, Mahmuda Naznin, Md. Atiqul Islam.

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Presentation transcript:

Energy-efficient Multiple Targets Tracking Using Target Kinematics in Wireless Sensor Networks Akond Ashfaque Ur Rahman, Mahmuda Naznin, Md. Atiqul Islam Mollah Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka, Bangladesh SENSORCOMM 2010

Outline Introduction System architecture & Preliminaries KBTMT algorithm Evaluation and Comparison Conclusion

Introduction Target tracking is one of the cardinal applications of a wireless sensor network. Nowadays, from military applications the use of sensor networks has extended to many civilian, industrial and environmental applications. ◦ Battlefield surveillance ◦ Intelligence data acquisition

Introduction The primary tasks of a sensor network are ◦ targets’ identification ◦ classification ◦ data acquisition ◦ targets’ tracking ◦ localizing ◦ data transmission

Introduction Due to power constraint and frequent connectivity failure of a sensor network, energy-efficient target tracking is a very challenging problem in the domain of sensor networks.

Goal A target tracking methodology is desired to track all targets efficiently, regardless of their types or numbers. Besides, it should minimize the energy consumption. Propose a novel, distributed, energy efficient multiple targets tracking method which includes ◦ target classification ◦ data acquisition ◦ Transmission ◦ Balances the traffic load

System architecture & Preliminaries Boundary Node(BN) Worker Node(WN) Computational Node(CN) Network Field

System architecture & Preliminaries Boundary Node(BN) ◦ Detection Worker Node(WN) ◦ Track targets ◦ Send information to the CN Computational Node(CN) ◦ Calculations for detection, classification, tracking and sleep-wake scheduling of the low powered sensor nodes.

System architecture & Preliminaries Definition : ◦ A. Traverse Region ◦ B. Refresh Time ◦ C. Polygon of Interest – target kinematics ◦ D. Overlapped Area of Interest Target Traverse Region Target Polygon of Interest Target Overlapped Area of Interest

KBTMT algorithm Tracking information ◦ Speed, Velocity, Time, Angle Four target types ◦ tracked vehicle, wheel vehicle, biological entity, animal CN WN Tracking info. Analysis target types Polygon of Interest Target

Overlapped Area of Interest Target WN Overlapped Area of Interest WN ? ? ? ?

Overlapped Area of Interest Case 1 Case 2 Case 3

Overlapped Area of Interest Case 1 Polygon of Interest

Overlapped Area of Interest Case 2

Overlapped Area of Interest Case 3 Unchanged

Evaluation and Comparison

Comparison of energy consumption at CNs.

Evaluation and Comparison Comparison of energy consumption at WNs.

Evaluation and Comparison Comparison of total energy consumption in the sensor network

Conclusion This paper propose a distributed energy efficient tracking method for tracking multiple targets in a large scale sensor network. In future, we would like to incorporate some other network properties like ◦ radio propagation model ◦ signal strength ◦ fault model in our tracking algorithm.