Live Object Detection and Fire Monitoring for Enhanced Agricultural Security System

Abstract

The agricultural industry plays a vital role in ensuring food security and economic stability. However, agricultural operations face numerous challenges, including animal theft, trespassing and the risk of fire outbreaks, which can lead to substantial financial losses and compromised food production. Existing security systems often rely on static cameras, which lack real-time monitoring capabilities and struggle to detect specific objects of interest, such as animals or fire, promptly. Therefore, there is a critical need to develop an advanced agricultural security system that incorporates live object detection and fire monitoring to mitigate these challenges effectively. This research work aims to develop an innovative solution by using a combination of live object detection and fire monitoring techniques to enhance the agricultural security system. By leveraging the Telegram API for efficient communication and integrating customised modifications into the OpenCV model, this study addresses the need for real-time identification of animals and early detection of fire incidents in agricultural environments.