AI-Based Real-Time Animal Detection and Alert System for Nighttime Road Safety
DOI:
https://doi.org/10.15662/IJEETR.2026.0802432Keywords:
Animal Detection, Highway Safety, Night-Vision Camera, Deep Learning, Convolutional Neural Networks (CNN), YOLO, Real-Time Alert System, Road Accident PreventionAbstract
Unexpected animal crossings on the road are a serious risk, especially at night when visibility is poor. The suggested solution includes an intelligent animal identification and alert framework with the goal of improving road safety through ongoing monitoring in order to address this issue. The system makes use of a high-resolution night-vision camera to record traffic in real time, allowing for round-the-clock monitoring under difficult circumstances. Even in dim or hazy conditions, deep learning methods like You Only Look Once (YOLO) and Convolutional Neural Networks (CNN) are used to reliably identify animals. The device lowers the chance of collisions by instantly sending out alarm signals to warn oncoming cars upon detection. This automated method reduces human interaction and offers a scalable solution appropriate for rural and highway roads. The integration of AI-based vision technology with real-time detection ensures rapid response and efficient performance. The suggested solution seeks to greatly lower animal-related traffic accidents and increase nighttime driving safety by fusing automation, deep learning, and proactive alert systems.
References
Road Accident Prevention
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