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Sensors 2018, 18(1), 11; doi:10.3390/s18010011

Time Series Analysis for Spatial Node Selection in Environment Monitoring Sensor Networks

1
School of ITEE, University of Queensland, Brisbane 4072, Australia
2
CSIRO/Data61, Pullenvale 4069, Australia
*
Author to whom correspondence should be addressed.
Received: 5 December 2017 / Revised: 20 December 2017 / Accepted: 20 December 2017 / Published: 22 December 2017
(This article belongs to the Special Issue Sensor Networks for Environmental Observations)
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Abstract

Wireless sensor networks are widely used in environmental monitoring. The number of sensor nodes to be deployed will vary depending on the desired spatio-temporal resolution. Selecting an optimal number, position and sampling rate for an array of sensor nodes in environmental monitoring is a challenging question. Most of the current solutions are either theoretical or simulation-based where the problems are tackled using random field theory, computational geometry or computer simulations, limiting their specificity to a given sensor deployment. Using an empirical dataset from a mine rehabilitation monitoring sensor network, this work proposes a data-driven approach where co-integrated time series analysis is used to select the number of sensors from a short-term deployment of a larger set of potential node positions. Analyses conducted on temperature time series show 75% of sensors are co-integrated. Using only 25% of the original nodes can generate a complete dataset within a 0.5 °C average error bound. Our data-driven approach to sensor position selection is applicable for spatiotemporal monitoring of spatially correlated environmental parameters to minimize deployment cost without compromising data resolution. View Full-Text
Keywords: wireless sensor networks; time series analysis; spatio-temporal analysis; environmental monitoring wireless sensor networks; time series analysis; spatio-temporal analysis; environmental monitoring
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Bhandari, S.; Bergmann, N.; Jurdak, R.; Kusy, B. Time Series Analysis for Spatial Node Selection in Environment Monitoring Sensor Networks. Sensors 2018, 18, 11.

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