PDF(Pubmed)
Abstract：
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.
摘要：
迅速隔离疑似病例,控制疫情,本研究提出了一种基于物联网（IoT）架构的体温监测系统。收集的数据通过无线通信传输到后端平台。使用分析的数据，该平台提供服务，例如任何异常的即时警报，传染病暴发预测,和给定区域的风险水平评估，对防疫有很大帮助。在一系列广泛的实验下，拟议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，分别。结果表明，在考虑环境温度的特定校准后，系统中的热成像传感器测量的体温可以准确地表示实际体温。它还可以扩展为决策支持系统，以帮助学校或政府机构做出适当的决定，以阻止传染病的传播。
