LORA Based Forest Fire Monitoring System

Abstract

The LoRa-based forest fire monitoring method by using wireless type networks is an IoT system designed to detect and prevent forest fires. The system consists of sensor nodes which are deployed throughout the forest to monitor various environmental conditions such as humidity, temperature, wind speed and direction. These sensor nodes are equipped with LoRa radios that enable them to communicate wirelessly with a central gateway. The Gateway gathers the data from the sensor nodes and transmits it to a server in the cloud for processing and analysis. The system utilizes machine learning algorithms to analyse the collected data and detect any anomalies that may indicate the forest fire. In the event of a fire, the system can alert local authorities and fire departments, providing them with real-time information about the location and severity of the fire. This allows for faster response times and more efficient management of the fire. The LoRa-based forest fire prevention system using wireless networks offers several advantages over traditional forest fire detection systems. Its low-power, long-range capabilities enable it to cover large areas, making it ideal for monitoring vast forested areas. Additionally, its wireless connectivity eliminates the need for physical infrastructure such as cables, which can be expensive and time-consuming to install. Overall, the LoRa-based forest fire prevention system using wireless networks is a promising solution for preventing and managing forest fires. Its innovative use of IoT technology and machine learning algorithms can help to reduce the impact of forest fires and protect both human life and the environment.