e-space
Manchester Metropolitan University's Research Repository

Location Prediction Optimisation in WSN Using Kriging Interpolation

Ikpehai, A and Adebisi, B and Ali, A and Mihaylova, L (2016) Location Prediction Optimisation in WSN Using Kriging Interpolation. IET Wireless Sensor Systems, 6 (3). pp. 74-81. ISSN 2043-6386

[img]
Preview

Download (627kB) | Preview

Abstract

Many wireless sensor network (WSN) applications rely on precise location or distance information. Despite the potentials of WSNs, efficient location prediction is one of the subsisting challenges. This study presents novel prediction algorithms based on a Kriging interpolation technique. Given that each sensor is aware of its location only, the aims of this work are to accurately predict the temperature at uncovered areas and estimate positions of heat sources. By taking few measurements within the field of interest and by using Kriging interpolation to iteratively enhance predictions of temperature and location of heat sources in uncovered regions, the degree of accuracy is significantly improved. Following a range of independent Monte Carlo runs in different experiments, it is shown through a comparative analysis that the proposed algorithm delivers approximately 98% prediction accuracy.

Impact and Reach

Statistics

Downloads
Activity Overview
117Downloads
51Hits

Additional statistics for this dataset are available via IRStats2.

Altmetric

Actions (login required)

Edit Item Edit Item