A Survey on Farm Protection Systems

Abstract—Wild animal intrusion poses a significant and persistent threat to agricultural productivity, particularly in rural and forest- adjacent areas. This paper presents a detailed comparative survey of different research studies that propose smart protection systems to deter animal intrusions using modern technologies such as the Internet of Things (IoT), Wireless Sensor Networks (WSN), Artificial Intelligence (AI), image processing, and geofencing. The reviewed systems encompass a variety of detection mechanisms—including PIR, ultrasonic sensors, computer vision, RFID tagging, and circuit- based triggers—and deploy deterrents ranging from sound and light to real-time alerts and virtual fencing. Each system is evaluated for its technical design, effectiveness, scalability, power efficiency, cost, and ethical considerations. Although many demonstrate innovation in theory, gaps remain in environmental robustness, large-scale deployment, and experimental validation. The paper concludes by identifying opportunities for hybrid, energy- aware solutions that balance technological sophistication with practical feasibility for farmers. This work aims to inform future research and policy in precision agriculture and wildlife management. Keywords—Wild animal intrusion, IoT, machine learning, crop protection, artificial intelligence, wireless sensor networks, virtual fencing, farm security, GSM, RFID.