The COVID-19 pandemic has highlighted the need for innovative solutions to monitor and control the spread of infectious diseases. With the potential for future pandemics and the risk of outbreaks particularly in academic institutions, there is a pressing need for effective approaches to monitor and manage such diseases. Contact tracing using Global Positioning Systems (GPS) has been found to be the most prevalent method to detect and tackle the extent of outbreaks during the pandemic. However, these services suffer from the inherent problems of infringement of data privacy that creates hindrance in adoption of the technology. Non-cellular wireless technologies on the other hand are well-suited to provide secure contact tracing methods. Such approaches integrated with the Internet of Things (IoT) have a great potential to aid in the fight against any type of infectious diseases. In response, we present a unique approach that utilizes an IoT based generic framework to identify individuals who may have been exposed to the virus, using contact tracing methods, without compromising the privacy aspect. We develop the architecture of our platform, including both the frontend and backend components, and demonstrate its effectiveness in identifying potential COVID-19 exposures (as a test case) through a proof-of-concept implementation. We also implement and verify a prototype of the device. Our framework is easily deployable and can be scaled up as needed with the existing infrastructure.

翻译：COVID-19疫情凸显了创新解决方案在监测和控制传染病传播方面的必要性。鉴于未来可能发生大流行以及学术机构等场所面临疫情暴发风险，亟需有效方法来监测和管理此类疾病。基于全球定位系统（GPS）的接触追踪已被视为疫情期间检测并应对疫情扩散范围的最常用方法。然而，这些服务存在数据隐私侵犯这一固有问题，阻碍了技术的普及。另一方面，非蜂窝无线技术非常适合提供安全的接触追踪方法。此类方法与物联网（IoT）集成，在协助对抗各类传染病方面具有巨大潜力。为此，我们提出了一种独特方法，利用基于物联网的通用框架，通过接触追踪技术识别可能接触病毒的个人，同时不损害隐私。我们开发了该平台的架构（包括前端和后端组件），并通过概念验证实施，以COVID-19暴露识别为测试案例，证明了其有效性。我们还实现并验证了设备的原型。该框架易于部署，并可在现有基础设施基础上按需扩展。