IOT BASED AUTOMATIC FOREST FIRE DETECTION BASED ON MACHINE LEARNING APPROACH

There are many applications for monitoring the environment thanks to the development of wireless sensor networks and the Internet of Things. As a possible use case for WSNs and the Internet of Things, we investigated the issue of monitoring and detecting forest fires in this paper. The current environmental damage is mostly caused by forest fires. The current forest fire monitoring system falls short in its ability to continuously provide real-time monitoring for every location within a target region and to facilitate early danger identification. Forest fires pose a significant hazard to the ecosystem as a whole, contributing to both global warming and ozone layer loss. The potential answer to decrease the cause or the danger of a fire occurrence by up to 95% is early detection. There are several strategies that may be used to keep woodlands fire-free. The technologies that may be helpful for the early identification of forest fires include satellite systems and unmanned aerial vehicles. Although these systems are capable of covering any geographical area, they are unable to provide real-time information on the full region of interest. Additionally, satellite-based and UAV-based systems are only suitable for monitoring and battling fires. Therefore, it is very vital to make accurate predictions of forest fires at an early stage.