The increasing frequency of leopard encounters near human settlements poses critical challenges to public safety and wildlife conservation. This research presents an AI-powered Leopard Detection and Alert System leveraging the YOLOv11 deep learning model and Internet of Things (IoT) technologies. The system performs real-time detection of leopards from surveillance footage and generates instant multi-channel alerts via the Telegram Bot API and an Arduino Uno R3-based piezoelectric buzzer. Experimental results demonstrate detection accuracy with confidence scores of 77–81%, real-time processing at 15–20 FPS, and overall system reliability, making the solution suitable for deployment in forest-border and rural regions. The modular architecture supports future extension to multi-species detection and edge device deployment.
Vikas et al. (Wed,) studied this question.