Animal Regognition and Repellent System for Smart Farming Using AI and Deep Learning:

The automation of horticulture has been progressing rapidly, with Deep Neural Networks (DNN) and the Internet of Things (IoT) being utilized for precise monitoring, control, and tracking across various applications. However, managing interactions with external factors in the agricultural ecosystem, particularly wildlife, remains a critical challenge. One of the major concerns for modern farmers is safeguarding crops from wild animal intrusions. Traditional solutions range from lethal methods (e.g., shooting) to non-lethal strategies (e.g., trapping, scarecrows, chemical deterrents, natural repellents, mesh barriers, or electric fences). However, some of these conventional approaches pose environmental hazards to both humans and wildlife, while others are expensive, require extensive maintenance.This paper introduces a system that integrates AI-driven Computer Vision and Deep Convolutional Neural Networks (DCNN) to identify and detect different animal species. It also employs species-specific ultrasonic signals to deter detected animals efficiently.