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@article{206677,
        author = {Prof. Nithya B P and Prof. Nivin K S and Janma A Saragodu and Vanashree and K Dhyan Samaga and Bhargavi Kulkarni},
        title = {RakshaNetra: Real-Time Animal Detection & Alert Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {151-158},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206677},
        abstract = {Human wildlife conflict is rising as natural habitats shrink and human settlements move closer to forest areas. Wild animals like elephants, leopards, and wild boars often enter villages and farms, leading to crop damage, property loss, and dangers to human safety. Many existing monitoring methods do not provide timely alerts, which results in delayed responses during intrusion events. This paper presents RakshaNetra, a real-time animal intrusion detection and alert system based on deep learning and edge computing. The system continually monitors live video feeds from surveillance cameras. It uses an object detection model to identify and classify wild animals in real time. When it detects an intrusion, it sends instant alerts with images and timestamps to the relevant authorities for quick action. Experimental evaluation shows that the system performs reliably in different lighting and environmental conditions. RakshaNetra offers a cost-effective, non-invasive, and scalable solution to help reduce human wildlife conflict and improve safety in forest-border areas.},
        keywords = {Human wildlife conflict, Animal intrusion detection, Deep learning, Computer vision, Edge computing, Real-time alert system.},
        month = {July},
        }