Human presence detection system - Tai, Xi Yang (2024)

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This paper presents the development and evaluation of an IoT-based human presence detection system leveraging microwave sensors. Traditional methods of monitoring human activity in buildings are often slow, inefficient, and costly. To address these challenges, this project aimed to create a cost-effective solution that offers real-time updates on human presence while addressing privacy concerns. The system architecture includes microwave sensors for improved accuracy and reliability, ESP32 microcontrollers for data processing, and cloud-based platforms such as AWS IoT Core, Timestream, and Grafana for data storage and visualization. Through meticulous design and integration, the system provides real-time detection of human presence. Moreover, the project delves into the critical aspect of determining optimal delay intervals for sensor status checks. Rigorous testing and experimentation were conducted to establish the most effective delay interval, ensuring reliable detection while minimizing false alarms. Additionally, the development of an automated calculation algorithm streamlines the testing process and enhances data collection efficiency. Challenges encountered during the project include addressing sensor faults, environmental interference, and optimizing hardware and software components also have been discussed. Overall, the project contributes valuable insights into the development of IoT-based human presence detection systems, paving the way for applications in occupancy monitoring and resource optimization.