Multi-Object Tracking in Wireless Sensor Networks Using Swarm Intelligence

Abstract

Wireless sensor networks (WSNs) may be described as a self-configured wireless networks that can be used to track physical objects or monitor environmental features, such as temperature or motion. The sensed data is then passed across the network to the main location or sink node, where the data can be processed and analyzed. Sensor nodes in WSN are fundamentally resource-constrained: they have restricted processing power, computing, space, and transmission bandwidth. Object tracking is considered as one of the major applications. However, many of the recent articles focused on object localization. In this chapter, the authors suggest an effective approach for tracking objects in WSNs. The aim is to achieve both minimal energy consumption in reporting activity and balanced energy consumption across the WSN lifetime extension of sensor nodes. Furthermore, data reliability is considered in our model. The chapter starts by formulating the multi-object tracking problem using 0/1 Integer Linear programming. In addition, the authors adopted the swarm intelligence technique to solve the optimization problem.