Farm Eye Raspberry PI and YOLO Based Animal Detector

The “Farm Eye” project presents a smart, real-time animal detection system utilizing Raspberry Pi and YOLOv3 for enhanced farm security. Designed to protect agricultural fields and property from stray or wild animals, this system combines computer vision with loT capabilities for efficient monitoring and alerting. At its core, a Raspberry Pi 4B processes live video feeds from a Pi Camera Module, leveraging the YOLOv3 deep learning model to detect animals accurately in various lighting conditions, including nighttime scenarios using infrared vision. Upon detecting an animal, the system triggers multiple alerts: a visual alert through an LED, an audible deterrent using a dog barking sound via speakers, and notifications sent through email and WhatsApp using Python-based automation. The YOLOv3 model, configured with pre-trained weights and class labels (coco.names), ensures high detection accuracy for commonly encountered animals in farm environments. Additionally, the system connects to the ThinkNet cloud platform to log and monitor detection events for remote access and analysis. Software support includes Python 3.7+, OpenCV, Pygame for sound output, and Picamera2 for interfacing the camera with the Raspberry Pi. GPIO is used for hardware interfacing, and the system is powered by a 5V, 3A adapter. The solution is cost-effective, scalable, and ideal for smart agriculture, minimizing human supervision while ensuring round-the-clock protection. By integrating real-time object detection, cloud computing, and loT communication protocols, “Farm Eye” demonstrates a practical and intelligent approach to automated animal detection and farm security.