A machine learning technique called “deep learning” teaches computers to do tasks more efficiently. For some tasks, artificial intelligence matches human intelligence. Neural networks are trained to accomplish this. In computer vision object detection and classification are the two effective tasks. Object detection is divided into two stages: one for single-stage detection and another for two-stage detection is one of the primary tasks of deep learning. In this research, we developed a real-time object detection system that can identify pedestrians and cars on our university campus, enabling the use of surveillance and monitoring. This is accomplished by combining a Raspberry Pi module hardware interface with the state-of-the-art “You Only Look Once” (YOLO Version 8) algorithm, which is a single-stage detector, to produce an effective real-time performance with an output result efficiency of 98.4%.