Innovative AI Solutions with Animal Detection for Road Safety and Preventing Wildlife Collisions

Wildlife-vehicle collisions (WVCs) are emerging as a serious concern for road safety. Advanced technologies, such as AI algorithms, IoV frameworks, and multi-sensor systems, provide promising solutions to these situations by detecting animals and alerting drivers. We studied a wide variety of techniques, such as CNNs, YOLO algorithms, and other real-time animal detection frameworks. This paper compares in depth the strengths and limitations of the current solutions in terms of accuracy, speed, and adaptability to different environmental conditions. This paper outlines the opportunities for research in enhancing detection accuracy, reducing false positives, and enabling large-scale implementation through IoV frameworks. This study can foster future interdisciplinary innovation.