The AI-Based Real-Time Face Tracking and Following Camera using Raspberry Pi is an intelligent embeddedvisionsystem designed to automatically detect, track, and follow a human face in real time. Traditional camera systems requiremanualpositioning and constant adjustment, which limits their effectiveness in dynamic environments such as surveillance, videoconferencing, robotics, and human–machine interaction. This project addresses these limitations by integratingartificialintelligence with compact, low-cost hardware to achieve autonomous camera control. The system is built around a Raspberry Pi, which serves as the main processing and control unit. A camera module continuouslycaptures live video frames and forwards them to the Raspberry Pi for processing. Face detection and tracking are performedusingAI and machine learning techniques implemented through TensorFlow and OpenCV. By analyzing each frame, thesystemidentifies facial features and calculates the position of the face relative to the camera’s field of view. Based on this information,control signals are generated to drive servo motors, enabling the camera to pan and tilt smoothly so that the detectedfaceremainscentered. The proposed system demonstrates real-time performance while maintaining low power consumption and cost efficiency, makingitsuitable for both academic and practical applications. The modular design allows for easy scalability and integrationwithadditional features such as multiple face tracking, face recognition, or IoT-based remote monitoring. Experimental resultsshowthat the system can accurately track moving faces under varying lighting conditions with minimal delay. Overall, the AI-based face tracking and following camera using Raspberry Pi highlights the potential of combiningembeddedsystems with artificial intelligence to create smart, autonomous vision solutions. This project provides a strong foundationforfuture advancements in intelligent surveillance, robotics, and interactive camera systems. Keywords: Artificial Intelligence, Computer Vision, Face Detection, Face Tracking, Haar Cascade, OpenCV, RaspberryPi, Real-Time Processing, Servo Motors, TensorFlows