MOCHA: Mobile Check-in Application for University Campuses Beyond COVID-19

Users and operators of shared spaces must ensure safety in such areas to prevent the spread of COVID-19. Although each organization has operated a variety of safety-related systems, including contact tracing, congestion monitoring, and check-in services, it is unclear what elements, such as privacy protection level, benefits, and permission procedures, have promoted the usage of these systems. In this study, we created MOCHA, a platform for sharing and tracking room-level locations. This platform automatically detects visited places by scanning Bluetooth beacons in each room using smartphones and shares location data according to predefined user settings. The collected data is used for room-level contact tracing, congestion monitoring, and reservation services. According to >6,500 users' usage data for a year in a university, outlining the advantages of utilizing the app encouraged people to install the app, and reinforced connections in small private groups are encouraged to use the app continuously. © 2022 ACM.

X-Fidence: Post-Pandemic Wellness By Density Monitoring with Privacy Preservation

There is an increasing interest in crowd monitoring as we return to normal life after the Covid-19 pandemic. Some major obstacles to implementing a monitoring system are: privacy, scalability, and accuracy. Several entities have developed their own branded safety reassurance programs using the Internet of Things and sensors during the pandemic, and many cities are planning for the post-pandemic era. However, the lack of inclusiveness and the fear of personal information leakage often limit their usage. To this end, we developed X-Fidence, a real-time density monitoring system to avoid crowds which preserves user privacy. X-Fidence anonymously tracks visitors in certain places using Bluetooth technology. The system consists of a signal receiver module, a mobile application, and a monitoring server where the citywide current occupancy data syncs automatically. The mobile application provides density data in real-time and average historic crowds information that helps to make decisions more confidently. The X-Fidence mobile app warns residents if any area experiences more visitors than maximum safe capacity. We also present our results from an experiment to measure the feasibility and accuracy of the system. © 2022 IEEE.

Design and Implementation of an Indoor Warning System with Physiological Signal Monitoring for People Isolated at Home.

Due to the recent COVID-19 pandemic, many people have faced in-home isolation, as every suspected patient must stay at home. The behavior of such isolated people needs to be monitored to ensure that they are staying at home. Using a camera is a very practical method. However, smart bracelets are more convenient when personal privacy is a concern or when the blood oxygen value or heart rate must be monitored. In this study, a low-cost indoor positioning system that uses a Bluetooth beacon, a smart bracelet, and an embedded system is proposed. In addition to monitoring whether a person living alone is active in a specific environment and tracking the heart rate or blood oxygen value under particular conditions, this system can also send early warning signals to specific observation units or relatives through instant messaging software.