• Dr.Venumadhava.M
• K Bhoomika
• Lekha Sahiti P
• M.N.Tejashwini
• Sahana.M

Wildlife conservation faces increasing challenges due to habitat destruction, climate change, poaching, and human encroachment. Traditional wildlife tracking techniques such as direct observation, tagging, and radio telemetry are often intrusive, expensive, and limited in scalability. This paper presents a Smart Wildlife Tracking System using Artificial Intelligence (AI) and the Internet of Things (IoT) for real-time, non-intrusive species monitoring in remote forest environments. The proposed system integrates a Raspberry Pi-based embedded platform with a Passive Infrared (PIR) sensor, camera module, GPS unit, and low-power wireless communication modules such as LoRa or GSM. A YOLOv5 deep learning model is employed for real-time wildlife species detection and classification from captured images. Upon detecting motion, the system captures images, identifies the species locally, records geolocation data, and transmits the information to a cloud-based platform for visualization and analysis. The system is powered by solar energy, ensuring sustainability and long-term autonomous operation. The proposed solution reduces the need for physical tagging, minimizes human interference, and provides accurate, real-time wildlife data. This system can significantly aid biodiversity monitoring, migration analysis, anti-poaching surveillance, and ecological research, contributing to smarter and sustainable wildlife conservation efforts.

Wildlife Tracking, Artificial Intelligence, IoT, YOLOv5, GPS, Smart Sensors, Conservation Technology

"Smart Wildlife Tracking System Using AI and IoT for Real-Time Species Monitoring ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.b496-b500, January-2026, Available :http://www.jetir.org/papers/JETIR2601172.pdf

"Smart Wildlife Tracking System Using AI and IoT for Real-Time Species Monitoring ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. ppb496-b500, January-2026, Available at : http://www.jetir.org/papers/JETIR2601172.pdf