This project introduces a wildlife protection by detecting and defensing poachers in real time in a novel turrent system. Using IoT and computer vision technologies, the system integrates high-resolution cameras and the Haar Cascade algorithm to accurately distinguish between humans and animals, significantly enhancing detection precision. Compared to this infill systems, which focuses on animal tracking and species identification using IoT sensors and the Random Forest algorithm, this project expands on real-time protection by incorporating immediate response mechanisms. While the base paper's system excels at monitoring and classifying animal behavior, it lacks direct countermeasures against poachers. Proposed system fills this gap by utilizing embedded platforms like Arduino and Raspberry Pi to control the turret’s movements and fire non-lethal rounds, temporarily incapacitating intruders without causing permanent harm. Unlike systems that rely solely on species monitoring, this project offers a proactive, scalable solution for wildlife conservation, ensuring continuous protection across varying environmental conditions, day or night. The system’s integration of real-time image recognition and automated deterrence establishes it as a more comprehensive approach to combating poaching.