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@article{201715,
        author = {ANJANA KUMARI and SACHIN SHRIRAM MAHULKAR and ANJALI YOGENDRA YADAV and NIKITA SANTOSH BANGAR},
        title = {IOT-Based Wildlife Movement Monitoring System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {5164-5166},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201715},
        abstract = {Human-Wildlife Conflict (HWC) and poaching pose significant threats to ecological sustainability and human safety, particularly near infrastructure like railways and highways. This paper presents a novel, real-time IoT-based Wildlife Movement Monitoring System de-signed for continuous surveillance and proactive risk mitigation. The system leverages advanced **thermal sensing** combined with a **Machine Learning (ML) classifier** (specifically a Convolutional Neural Network or CNN) to analyze thermal signatures, accurately categorize species, and predict directional movement. This approach provides a non-intrusive, continuous, and highly accurate alternative to traditional tracking methods, aiming to enhance conservation efforts and prevent HWC-related accidents by enabling timely intervention.},
        keywords = {IoT, Human-Wildlife Conflict (HWC), Thermal Sensing, Machine Learning (ML), Real-Time Alerting, Non-intrusive Monitoring, Edge Computing.},
        month = {May},
        }