IoT based Sensor System Design for Real-Time Non-Intrusive Occupancy Monitoring

Veena Chidurala, Xiaodong Wang, Xinrong Li, Jesse H. Hamner
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Abstract

The sensor systems are growing daily in terms of their complexity and getting more sophisticated from an application perspective. Smart cities and intelligent buildings are critical driving factors in designing and improving sensor systems. However, there is always a big concern about invading people’s privacy and finding the right balance between privacy and sensing accuracy. In our previous work, we demonstrated how thermal imaging sensors could estimate occupancy effectively in a non-intrusive way. This paper presents an efficient sensor system design of a non-intrusive occupancy monitoring system (OMS). It uses state-of-the-art open-source software elements such as the FastAPI web framework, Raspberry Pi, low-resolution IR thermal sensor, temperature, humidity, and motion sensors. We also present our data collection methods in detail and show valuable insights and experimental results to demonstrate that our OMS can accurately estimate the occupancy in a designated area or a room level to meet various demanding real-time occupancy monitoring applications.
基于物联网的实时非侵入式占用监测传感器系统设计
传感器系统的复杂性与日俱增,从应用的角度来看也越来越复杂。智能城市和智能建筑是设计和改进传感器系统的关键驱动因素。然而,如何侵犯人们的隐私,如何在隐私和传感精度之间找到适当的平衡,一直是人们关注的问题。在我们之前的工作中,我们展示了热成像传感器如何以非侵入式的方式有效地估计占用率。本文提出了一种高效的非侵入式占用监测系统(OMS)传感器系统设计。它使用最先进的开源软件元素,如FastAPI web框架、树莓派、低分辨率红外热传感器、温度、湿度和运动传感器。我们还详细介绍了我们的数据收集方法,并展示了有价值的见解和实验结果,以证明我们的OMS可以准确地估计指定区域或房间级别的入住率,以满足各种苛刻的实时入住率监控应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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