It is a challenging task to develop a model which detects intruders and injured animals in reserved forests. In some cases, forest guards driven by monetary incentives or bribes, may permit intruders to enter restricted zones for hunting, posing a serious threat to wildlife. Furthermore, such negligence often extends to the well-being of animals, as injured or distressed wildlife frequently go unnoticed and fail to receive timely medical attention. In this paper, we propose a new YOLO (You Only Look Once) algorithm which is extensively used for object detection. Due to the latest technology and advanced features embedded in it, the performance for wildlife monitoring and intrusion detection in reserved forests/ protected wildlife areas is improved to a larger extent. The model achieves an accuracy of 88%, demonstrating its reliability in real-time detection scenarios. The model on which we are working basically addresses the issue of hunting and poaching in reserved forests. It takes real-time images from CCTV cameras installed in the reserved forests and using the latest algorithm YOLO (version v8), it detects the humans (intruders) and prevents poaching/ hunting by sending emergency alerts to the security. Furthermore, the model also detects whether an animal is injured or not and ensures immediate medical assistance is provided if needed. This approach offers a cost-effective and efficient solution for enhancing wildlife protection using real-time computer vision technology.