Object tracking with an AIS-inspired algorithm

Abstract

Wireless Sensor Networks (WSNs) provide an effective means to perform data acquisition in remote areas. However, limitations exist that prohibit their widespread use. In this paper, an object tracking algorithm based on Artificial Immune Systems (AIS) is proposed. Based on the immune network theory of AIS, the activities of wireless sensor nodes are stimulated by target in-coming objects but suppressed by other wireless sensor nodes based on a dynamic changing environment. When a sensor node is being suppressed, the sensor node will go to a low-power state momentarily, otherwise, it will be actively estimating the location of the target objects. In doing so, the energy efficiency of the overall network will be optimized through the dynamic stimulation and suppression of sensor nodes that is mediated by the immunity-based algorithm. A number of experiments are conducted to verify the algorithm in terms of the degree of accuracy in target tracking and the energy efficiency of the entire sensor network. © 2009 IEEE.