Abstract
In this paper, we propose an energy-efficient tracking algorithm for predicting the trajectory of a mobile radioactive target in a wireless sensor network. The sensor nodes are assumed to be capable of detecting the strength of the background radioactive radiations as well as the signals emanating from a mobile radiological dispersal device (RDD). As the individual RDD signals may not be easily distinguishable enough from the background radiation, we propose that each sensor node sum up the strength of the signals sensed in its neighborhood for a sampling time period, and then (at the end of this time period) forward the value of the sum of the signals sensed in the neighborhood to a control center (sink). The sink identifies the sensor nodes (suspect nodes) that report relatively larger values for the sum of the signal strengths that is different from those of others; the arithmetic mean of the X and Y coordinates of the suspect sensor nodes is predicted as the location of the RDD at a time instant corresponding to the middle of the sampling time period. We evaluate the difference between the predicted and exact locations of the RDD trajectory over time as a function of the different operating parameters (such as the RDD velocity, transmission and sensing range of the sensor nodes and the duration of the sampling time period) as well as evaluate the network lifetime and node lifetime incurred due to exhaustion of the energy levels of the sensor nodes.
Highlights
Wireless sensor networks (WSNs) have been used for several environmental monitoring applications
The tracking algorithm is data-centric and lets each sensor node to sum the strength of the radioactive signals sensed in the neighborhood and report the summed value over a sampling time period to the sink via a data gathering tree
The hypothesis is that the sensor nodes that report relatively larger value for the sum of the sensed signals are likely to be in the vicinity of the mobile target during the sampling time period - we use the average of the X and Y coordinates of the suspect sensor nodes as the predicted locations of the radioactive dispersal device (RDD)
Summary
Wireless sensor networks (WSNs) have been used for several environmental monitoring applications. The sink picks the top x sensor nodes (in our simulations x = 5 sensor nodes) that report sum values (for the radioactive signals in their neighborhood), which are the largest among those learnt from the sensor nodes We refer to these sensor nodes as the suspect sensor nodes in whose neighborhood the RDD is likely to be moving for the duration of the particular sampling time period. As the sensor nodes operate with limited battery charge, they are likely to run out of energy during the course of data aggregation and mobile target tracking. We identify the independent variables of the network and the operating environment to be parameters such as the velocity of the RDD, the transmission range (and in turn the sensing range) of the sensor nodes, and the sampling time period.
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