Monitoring System with Time Difference in Traffic Car, Motorcycle and Human Based Arduino with Motion Sensor

I Nyoman Gede Adrama, IMade Asna and Putu Ariawan
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I Nyoman Gede Adrama: Department of Electrical Engineering, Universitas Pendidikan Nasional, Denpasar, Indonesia
IMade Asna: Department of Electrical Engineering, Universitas Pendidikan Nasional, Denpasar, Indonesia
Putu Ariawan: Department of Electrical Engineering, Universitas Pendidikan Nasional, Denpasar, Indonesia

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 2, 386-395

Abstract: Traffic monitoring systems are an important component in managing the flow of vehicles and pedestrians in cities. This research develops and implements an Arduino-based traffic monitoring system using motion sensors (PIR) to detect cars, motorcycles, and humans. The system is designed to monitor and analyze the movement of different types of objects with the aim of improving traffic efficiency and safety. PIR sensors are used to detect changes in infrared radiation produced by objects moving in front of the sensor. The Arduino acts as the main controller that processes the data from the sensor and sends it to the server for further analysis. This study discusses the differences in detection characteristics between cars, motorcycles, and humans, as well as the challenges of optimizing sensor sensitivity for each type of object. The results of the implementation show that this system is able to detect and distinguish cars, motorcycles, and humans with adequate accuracy. The data obtained is used to identify traffic patterns and provide real-time information that can help traffic managers in decision-making. The system also offers a cost-effective and easy-to-implement solution, with the potential for further development for integration with more advanced IoT and data analytics technologies. Thus, this Arduino-based traffic monitoring system with motion sensors makes a significant contribution to more efficient and safe traffic flow management, and provides a solid foundation for further research and development in the field of smart transportation.

Date: 2025
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