Jiang Joe-Air, Wang Jen-Cheng, Hsieh Chao-Liang, Tseng Kai-Sheng, Ye Zheng-Wei, Su Lin-Kuei, Sun Chih-Hong, Wen Tzai-Hung, Juang Jehn-Yih
Department of Biomechatronics EngineeringNational Taiwan University Taipei 10617 Taiwan.
Department of Medical ResearchChina Medical University Hospital, China Medical University Taichung 40447 Taiwan.
IEEE Internet Things J. 2020 Oct 27;8(7):5778-5793. doi: 10.1109/JIOT.2020.3034024. eCollection 2021 Apr 1.
To quickly isolate suspected cases to control the epidemics, this study proposes a body temperature monitoring system with a thermography based on the Internet of Things (IoT) architecture. The collected data are transmitted to a back-end platform via wireless communication. Using the analyzed data, the platform provides services, such as instant alerts for any anomalies, infectious disease outbreak prediction, and risk level assessment for a given area, and it will be a great help to epidemic prevention. The mean absolute percentage error and root mean square error of the proposed monitoring system under an extensive series of experiments are 0.04% and 0.0204°C, respectively. It shows that the body temperature measured by the thermal imaging sensor in the system can accurately represent the actual body temperature after specific calibrations that take the environmental temperature into account. It can also be expanded to a decision supporting system to help schools or government agencies to make proper decisions to stop the spread of infectious diseases.
为了快速隔离疑似病例以控制疫情，本研究提出了一种基于物联网（IoT）架构的带有热成像的体温监测系统。收集到的数据通过无线通信传输到后端平台。利用分析后的数据，该平台提供诸如对任何异常情况的即时警报、传染病爆发预测以及给定区域的风险水平评估等服务，这将对疫情防控有很大帮助。在一系列广泛的实验中，所提出的监测系统的平均绝对百分比误差和均方根误差分别为0.04%和0.0204°C。这表明系统中的热成像传感器所测量的体温在考虑环境温度进行特定校准后能够准确代表实际体温。它还可以扩展为一个决策支持系统，以帮助学校或政府机构做出适当决策来阻止传染病的传播。
