Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W3, 41-46, 2014
https://doi.org/10.5194/isprsarchives-XL-2-W3-41-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
22 Oct 2014
ARIMA based Value Estimation in Wireless Sensor Networks
A. Amidi Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands
Keywords: Temporal correlation modelling, data smoothing, sample size, life span, outlier detection, energy efficiency Abstract. Due to the widespread inaccuracy of wireless sensor networks (WSNs) data, it is essential to ensure that the data is as complete, clean and precise as possible. To address data gaps and replace erroneous data, temporal correlation modelling can be applied, which takes advantage of temporal correlation and is also energy efficient. In this research, the suitability of adapting the ARIMA model into a WSN context is scrutinized, as technological requirements demand special considerations. The necessity of applying a smoothing technique is explored and the selection of an appropriate method is determined. Additionally, the available options with regards to ARIMA set-up are discussed, in terms of achieving accurate and energy friendly predictions. The effect of sufficient historical data and the importance of predictions’ life span on the estimation accuracy are additionally investigated. Finally, an adaptive, online and energy efficient system is proposed for maintaining the accuracy of the model that simultaneously detects outliers and events as well as substitutes any missing or erroneous data with estimated values.
Conference paper (PDF, 1849 KB)


Citation: Amidi, A.: ARIMA based Value Estimation in Wireless Sensor Networks, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W3, 41-46, https://doi.org/10.5194/isprsarchives-XL-2-W3-41-2014, 2014.

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