Amal H. Alharbi, Hanan A. Hosni Mahmoud^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6237-6252, 2022, DOI:10.32604/cmc.2022.030963

Abstract Hazardous incidences have significant influences on human life, and fire is one of the foremost causes of such hazard in most nations. Fire prediction and classification model from a set of fire images can decrease the risk of losing human lives and assets. Timely promotion of fire emergency can be of great aid. Therefore, construction of these prediction models is relevant and critical. This article proposes an operative fire prediction model that depends on a prediction unit embedded in the processor UDOO BOLT V8 hardware to predict fires in real time. A fire image database is improved to enhance the… More >

Haoran Zhu¹, Demin Gao^1,2,*, Shuo Zhang¹

Journal on Internet of Things, Vol.1, No.1, pp. 25-31, 2019, DOI: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… More >