Evolution of YOLO: Exploring the Advancements in YOLOv8 for Real-Time Wildlife Detection

In the context of wildlife conservation, this review paper critically evaluates the development of the YOLO (You Only Look Once) object detection framework with a focus on YOLO 8. Technology's role is crucial as biodiversity preservation becomes more and more important, making YOLO model improvements very pertinent. Our approach entails a thorough examination of YOLO's technical development from YOLO 6 to YOLO 8, highlighting significant improvements. We look at real-world examples to show how effective YOLO is at tasks like species identification, animal tracking, and poaching avoidance. We highlight the positive aspects of YOLO while also addressing implementation issues and offering strategic advice. In order to safeguard wildlife, we finish by summarizing upcoming trends and future research directions in computer vision.