Conference Paper

Tracking moving targets in a smart sensor network

Dept. of ECECS, Cincinnati Univ., OH, USA
DOI: 10.1109/VETECF.2003.1286181 Conference: Vehicular Technology Conference, 2003. VTC 2003-Fall. 2003 IEEE 58th, Volume: 5
Source: IEEE Xplore

ABSTRACT

Networks of small, densely distributed wireless sensor nodes are capable of solving a variety of collaborative problems such as monitoring and surveillance. We develop a simple algorithm that detects and tracks a moving target, and alerts sensor nodes along the projected path of the target. The algorithm involves only simple computation and localizes communication only to the nodes in the vicinity of the target and its projected course. The algorithm is evaluated on a small-scale testbed of Berkeley motes using a light source as the moving target. The performance results are presented emphasizing the accuracy of the technique, along with a discussion about our experience in using such a platform for target tracking experiments.

Full-text preview

Available from: cs.sunysb.edu
  • Source
    • "To our knowledge, the only work focused on light source tracking in sensor networks was presented by Gupta and Das [7]. Photo sensors are used as proximity sensors for detecting the light source target. "
    [Show abstract] [Hide abstract]
    ABSTRACT: We revisit the classic object tracking problem with a novel and effective, yet straightforward distributed solution for resource-lean devices. The difficulty of object tracking lies in the mismatch between the limited computational capacity of typical sensor nodes and the processing requirements of typical tracking algorithms. In this paper, we introduce an in-network system for tracking mobile objects using resource-lean sensors. The system is based on a distributed, dynamically-scoped tracking algorithm which alters the event detection region and reporting rate based on object speed. A leader node records the detected samples across the event region and estimates the object's location in situ. We study the performance of our tracking implementation on an 80-node test bed. The results show that it achieves high performance, even for very fast objects, and is readily implemented on resource-lean sensors. While the area is well-studied, the unique combination of algorithmic features represents a significant addition to the literature.
    Full-text · Conference Paper · May 2014
  • Source
    • "Target tracking is one of the key enabling techniques of wireless sensor networks in a variety of applications including security and surveillance, traffic management, wild animals tracking, and environmental monitoring [1] [2] [3] [4] [5] [6] [7] [8]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In emerging tracking systems using mobile wireless sensor networks, sensor mobility management is essential for balancing the tracking performance and costs under limited network resources and sensor movements. This paper considers the sensor mobility control problem for multitarget tracking (MTT), in which multiple mobile sensors are dynamically grouped and moved to track multiple targets and collaborate within each sensor group via track data fusion. A novel sensor mobility control framework for the mobile sensor network-based MTT is proposed. It is formulated as a constrained optimization problem that aims to maximize the overall tracking performance for all targets while conserving network energy and providing tracking coverage guarantee. The optimization problem is relaxed as a convex programming problem for computational tractability and its solution is implemented in a distributed manner. The newly proposed sensor mobility control scheme, implemented on the basis of iterative subgradient search, is shown via computer simulation to have better performance over the static sensor network-based MTT.
    Full-text · Article · Mar 2014 · International Journal of Distributed Sensor Networks
  • Source
    • "Most tracking protocols suggested up to now [1] [2] [3] [4] have not noticed the type of target mobility model sufficiently. In other words, is the efficiency of a tracking protocol the same when tracking a tank or a human? "

    Preview · Article · May 2011 · International Journal of Computer Applications
Show more