Real- Time Seat Occupancy Detection in Waiting Rooms using Arduino Nano 1oT 33

This study presents a seat occupancy detection system for waiting rooms utilizing the Arduino Nano IoT 33 platform. The primary aim is to create an affordable and scalable solution to accurately monitor seat occupancy in real-time, improve space management, and reduce waiting times in healthcare and public service settings. The system uses ultrasonic sensors to detect individuals sitting in seats, which are then connected to the IoT platform to provide real-time data to a central monitoring system. The system underwent testing in a simulated environment and demonstrated a high level of accuracy in detecting occupancy, with an error margin of less than 5%. Its modular design allows for easy expansion and integration with existing IT infrastructures, making it flexible for applications beyond waiting rooms, such as conference halls, classrooms, and public transport systems. The study also discusses the challenges associated with sensor accuracy, energy efficiency, and data privacy. It proposes potential solutions such as integrating additional sensor types, using energy-efficient IoT protocols, and complying with legal standards. The results indicate that the system can significantly improve the management of public spaces, providing a cost-effective tool for organizations to optimize space utilization and enhance user experience. This study contributes to the field of smart environments and demonstrates the potential of IoT technology in addressing practical challenges in public service management. Future work will focus on implementing machine learning algorithms to improve system accuracy and adaptability in dynamic environments.