Title: A decision tree algorithm for forest fire prediction based on wireless sensor networks

Authors: Demin Gao; Jie Xin; Fuquan Zhang

Addresses: College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China; Department of Computer Science and Engineering, University of Minnesota, Minneapolis MN, 55455, USA ' College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China ' College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China; The Electrical and Computer Engineering Department, McMaster University, Canada

Abstract: Forest fire poses a significant threat not only to the natural environment and ecological systems but also to the safety of human life and property. Combined with new technologies, a decision tree algorithm is proposed for forest fire prediction, in which wireless sensor networks technology is utilised to transmit data and predict the ignition of the forest. There are four meteorological parameters as part of training data, containing temperature, relative humidity, wind speed, and daily precipitation, while the other part is prediction results of Forest Weather Index system. The decision tree generated by our system could classify these parameters from the most significant to the least significant so that it can better foretell fire occurrence. The analysis of prediction results shows that our system is effective.

Keywords: decision tree algorithm; forest fire prediction; wireless sensor networks; WSNs.

DOI: 10.1504/IJES.2020.110656

International Journal of Embedded Systems, 2020 Vol.13 No.4, pp.422 - 430

Received: 21 Feb 2019
Accepted: 09 Sep 2019
Published online: 27 Oct 2020 *

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