Published Paper Details:

Wildlife conservation faces challenges due to deforestation, climate change, and human encroachment, leading to animal-vehicle collisions, habitat degradation, and wildfires. This project introduces an AI and IoT-based system for real-time wildlife monitoring and environmental assessment. It employs YOLO-based AI cameras to detect animal movements, integrating an automatic braking system in vehicles to prevent collisions. In case of an impact, the system instantly alerts the forest department with detailed incident data. To enhance habitat protection, flame and smoke sensors detect wildfires early, while soil sensors monitor moisture, pH, and nutrient levels to assess ecosystem health. An AI-driven leaf analysis module further enables early disease detection and stress assessment in plants. All data is processed in a real-time dashboard, generating automated alerts and insights for conservation authorities. By combining AI, IoT, and predictive analytics, this system provides an efficient, scalable, and automated approach to wildlife protection and habitat conservation.