In recent years, aged care living has drawn attention because of population aging and extension of average lifespan. Moreover, the rapid development of information communication technology and the internet of things lay the foundation for the application of sensor networks and cloud computing on medical care. Most elderly often suffer from chronic diseases due to weaker immunity causing a higher infection risk. The problem of infection controlling is an essential issue for residences living in aged care facilities. In the past, for infection control, medical personnel use the manual method of tracking, investigating, and interviewing patients to obtain patient contact list. This method cannot identify residents who have a high risk of infection, distinguish the distance between patients and other residents, and evaluate the risk of infection. To isolate all the residents who contact patients is the only solution that does not only cause repulsion of other residents but also waste medical resources. This study proposes a visual infection control positioning system for aged care facilities using the RFID (Radio Frequency Identification) technology and IoT technology. It can calculate the distance between users and reduce the positioning error. The system combines location fingerprinting with the K-nearest neighbor algorithm to fix errors caused by signal fluctuation of RFID to improve the positioning accuracy. The system records the indoor movement path of the residents in a real-time manner through the positioning function. When infectious diseases spread in aged care living residences, to help medical personnel, the system can screen out residents with a high risk of infection who closely contact with patients according to the movement path of the patients and other residents, and visually display them. For some infectious diseases, residents who live together with patients may be infected even if they do not have contact with the patients closely. This system can also identify the residents whose cumulative contact time exceeds the limit according to the medical definition of various infectious diseases and input time value.

近年来，由于人口老龄化和平均寿命的延长，老年护理生活引起了人们的关注。此外，信息通信技术和物联网的飞速发展为传感器网络和云计算在医疗上的应用奠定了基础。大多数老年人由于免疫力较弱而经常患有慢性疾病，从而导致较高的感染风险。对于居住在养老机构中的居民来说，感染控制的问题是必不可少的。过去，为了控制感染，医务人员使用手动方法来跟踪，调查和采访患者以获取患者联系人列表。这种方法无法识别出具有高感染风险的居民，区分患者与其他居民之间的距离以及评估感染的风险。隔离所有与患者接触的居民是唯一的解决方案，不仅会导致排斥其他居民，而且会浪费医疗资源。这项研究提出了一种使用RFID（射频识别）技术和IoT技术的老年护理设施视觉感染控制定位系统。它可以计算用户之间的距离并减少定位误差。该系统将位置指纹与K最近邻算法相结合，以解决由RFID信号波动引起的错误，从而提高定位精度。系统通过定位功能实时记录住户的室内运动路径。当传染病在养老院中传播时，为了帮助医务人员，该系统可以根据患者和其他居民的移动路径，筛选出与患者密切接触的高感染风险居民，并以视觉方式显示出来。对于某些传染性疾病，即使与患者生活在一起的居民即使没有与患者密切接触也可能被感染。该系统还可以根据各种传染病的医学定义和输入时间值来识别累积接触时间超过限制的居民。