Open Access

ARTICLE

A Perceptron Algorithm for Forest Fire Prediction Based on Wireless Sensor Networks

by Haoran Zhu¹, Demin Gao¹, Shuo Zhang¹

1 College of Information Science and Technology, Nanjing Forestry University, Nanjing , 210037, China.
2 Department of Computer Science and Engineering, University of Minnesota. Minneapolis MN, 55455, USA.

*Corresponding Author: Demin Gao. Email: .

Journal on Internet of Things 2019, 1(1), 25-31. https://doi.org/10.32604/jiot.2019.05897

Abstract

Forest fire prediction constitutes a significant component of forest management. Timely and accurate forest fire prediction will greatly reduce property and natural losses. A quick method to estimate forest fire hazard levels through known climatic conditions could make an effective improvement in forest fire prediction. This paper presents a description and analysis of a forest fire prediction methods based on machine learning, which adopts WSN (Wireless Sensor Networks) technology and perceptron algorithms to provide a reliable and rapid detection of potential forest fire. Weather data are gathered by sensors, and then forwarded to the server, where a fire hazard index can be calculated.

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Citations