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Copyright of Journal of Shanxi Agricultural Sciences is the property of Shanxi Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]