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Wildlife Monitoring System Using GSM System

Harshala Arvind Rajeshirke, Dr. A.S. Mali, Dr. S.T. Jadhav

Abstract


The increasing incidence of wild animal intrusion in agricultural areas poses significant risks to both human safety and crop productivity. This project, AI-IoT Smart Animal Surveillance for Human Safety, proposes a real-time monitoring system that integrates Artificial Intelligence (AI) with Internet of Things (IoT) to detect, alert, and assess the presence of wild animals near farms. The system utilises a Raspberry Pi equipped with a camera module and employs the YOLOv8 (You Only Look Once) object detection algorithm to accurately identify animals from live video feeds. Upon detection, the system captures the image, sends an email alert with timestamp and location to the farmer, and activates a buzzer to warn nearby individuals. Additionally, IoT-based health monitoring sensors such as temperature, heartbeat, and gas sensors are used to evaluate the physical condition and surrounding environment of the detected animals, aiding early detection of diseases or environmental threats.

The system operates in real-time and ensures quick response to critical situations, thereby minimizing crop damage and reducing the risk of human-animal conflicts. It is designed to be cost-effective, energy-efficient, and easy to deploy in rural and remote areas. Furthermore, the system can be enhanced with features such as mobile application integration, cloud-based data storage, and GPS tracking for better monitoring and control. Overall, the proposed system provides a smart, automated, and reliable solution for wildlife surveillance and safety management.


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