A Fog-based Smart Agriculture System to Detect Animal Intrusion

Smart agriculture is one of the most promising areas where IoT-enabled technologies have the potential to substantially improve the quality and quantity of the crops and reduce the operational cost. However, building a smart agriculture system presents several challenges, including high latency and bandwidth consumption associated with cloud computing, Internet disconnections in rural areas, and the need to keep costs low for farmers. To address these issues, this paper proposes a fog-based smart agriculture infrastructure with edge computing and LoRa communication. We address the top concern of farmers - animals intruding - by proposing a solution that detects animal intrusion using low-cost PIR sensors, cameras, and computer vision and predicts animal locations using a novel algorithm. Our system can detect animals before the intrusion, identify them, predict their future locations, and alert farmers promptly. The paper proposes three sensor layouts, and experiments confirm the system’s effectiveness and lower cost compared to state-of-the-art systems.