The design of an effective traffic counting system is crucial for improving traffic management in urban environments. This study aims to develop a traffic counting system that utilizes object detection through Internet of Things (IoT)-based cameras. The system employs the You Only Look Once (YOLO) algorithm for real-time vehicle detection, enabling high accuracy in vehicle identification and counting. In this design, a REST API architecture is implemented to ensure efficient data communication between the detection and storage modules, allowing for flexible and scalable data retrieval and analysis. Test results show that this system can provide quick and accurate information regarding traffic flow under various conditions. Thus, this research makes a significant contribution to the development of smart city technology and provides a useful tool for traffic analysis and decision-making.
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