Advancing Wildlife Conservation: AI-Driven Weight Estimation Drones for Accurate and Efficient Wildlife Management
Bodaballa Karthik, P Mithun, N Nikhil, Aditya Kulkarni, J L Srinivas, Sripad Kulkarni S · 2025
Accurate weight estimation of animals plays a pivotal role in wildlife management, veterinary care, and conservation efforts. Traditional methods, such as visual estimations by veterinarians, often result in approximate and inconsistent weight calculations, leading to potential problems in health monitoring, treatment effectiveness, and conservation planning. To address these challenges, the Weight Estimation Drone (WED) has been developed as a noninvasive, technology-driven solution. Equipped with advanced imaging sensors, LiDAR and AI-powered algorithms, WED captures precise 3D body measurements of animals from a safe distance, allowing accurate weight estimations. By processing these measurements through machine learning models, WED significantly reduces human error and enhances the accuracy of weight estimates. This project aims to advance wildlife health monitoring, improve conservation practices, and foster sustainable human-animal co-existence through precise data-driven approaches.