Prevention of fire and hunting in forests using machine learning for sustainable forest management

Abstract

Deforestation, illegal hunting, and forest fires are a few current issues that have an impact on the diversity and ecosystem of forests. To increase the biodiversity of species and ecosystems, it becomes imperative to preserve the forest. The conventional techniques employed to prevent these issues are costly, less effective, and insecure. The current systems are unreliable and use more energy. By utilizing an Internet of Things (IOT) system, this technology offers a more practical and economical method of continuously maintaining and monitoring the status of the forest. To guarantee excellent security, this system combines a number of sensors, alarms, cameras, lights, and microphones. It aids in reducing forest loss, animal trafficking, and forest fires. In the suggested system, sensors are used for monitoring, and cloud storage is used for data storage. Through the use of machine learning, the raspberry pi camera module significantly aids in the prevention of unlawful wildlife hunting as well as the detection and prevention of forest fires.