Title: Detection of an event and its location in a wireless sensor network

Authors: Tapan K. Nayak; Cheng Zhang

Addresses: Department of Statistics, George Washington University, Washington DC, 20052, USA ' Department of Statistics, George Washington University, Washington DC, 20052, USA

Abstract: Wireless sensor networks (WSNs), which can often be installed quickly and fairly economically, are useful for detecting threats (or events) in a region of interest. As the data received from sensor nodes contain measurement and transmission errors, interpreting the data requires appropriate statistical methods and algorithms. In particular, deciding if an event is present in the network region or not and inferring the location of the event when it is deemed present are two important decision problems. We give a statistical framework for addressing these two problems and frame them as one estimation problem. We present a solution based on the maximum likelihood method and evaluate its performance by simulation. We also describe a Bayesian approach that can be used when relevant prior distribution and loss function are available.

Keywords: estimation error; maximum likelihood; parameter estimation; sensor nodes; transmission errors; event detection; event location; wireless sensor networks; WSNs; simulation.

DOI: 10.1504/IJSNET.2017.080637

International Journal of Sensor Networks, 2017 Vol.23 No.1, pp.1 - 10

Accepted: 28 Jan 2016
Published online: 25 Nov 2016 *

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