  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.
