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@article{189222,
        author = {Guruprasanna J K and Rajath R Kumar and Rithesh U and Shreyas T S and Uttam},
        title = {Wild-Guard: A Smart Wild Animal Alert System for Roads in Network Covered Areas},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {7},
        pages = {8188-8191},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189222},
        abstract = {This paper presents an AI-enabled real-time alert system designed to prevent human–wildlife conflicts in forest and highway regions. The system utilizes computer vision and deep learning techniques, specifically the YOLOv8 model, to detect wild animals through roadside surveillance cameras. Upon detection, the animal snap- shot, GPS location, and timestamp are uploaded to Firebase, and alerts are delivered to nearby users through an Android mobile ap- plication via Firebase Cloud Messaging (FCM). The application provides voice alerts, emergency support, and live location sharing to enhance public safety. The approach offers a scalable, auto- mated, and real-time solution to reduce accidents and protect both humans and animals.},
        keywords = {Wild Animal Detection, YOLOv8, Real-Time Alert System, Firebase Cloud Messaging, Android Application, Computer Vision, Safety Monitoring.},
        month = {January},
        }