ACCESS (Advanced Computing and Communication Enabled Smart Society) Lab
Research Areas
5G and Beyond (B5G/6G) communication networks
Smart and Secure Health Care Systems
Secure and Smart Internet of Things (IoT)
Logic-in-Sensor
Deep Learning Applications for Communication, Computing and Medical Analytics (DL-CCMA)
Unmanned Aerial Vehicle (UAV)-based networks
Edge Computing
Smart and Secure Cyber Physical Systems (CPSs)
COVID-19 Smart, Privacy-Preserving Contact Tracing App
[ Demo video of the application prototype is available here]
ICT-based awareness, preparedness, and contact tracing helped only a few Asian countries efficiently contain the spread of COVID-19. Existing contact tracing models include cell tower-based location tracking, CCTV-based movement tracking using image recognition, and Bluetooth-based proximity alerts. However, they are not compliant with the national policy of North and South American countries such as Canada, Brazil, USA, and so forth.
Therefore, a new contact tracing model is essential that does not explicitly pull user data from cell phone operators or CCTV footage and compromise the patients’ privacy.
For this purpose, in this project, we develop a mobile application framework with four modules: ❶ questionnaire module, ❷ GPS location information module, ❸ gesture AI based check to detect home isolation/physical distance violation event, and ❹ share these encrypted information with remote servers using Private Information Retrieval (PIR) module.
Current Developer: Sadman Sakib, graduate student, smart communications laboratory at LU/TBRHRI.
The screenshots are available here.