The SRM Institute of Science and Technology (SRMIST), Kattankulathur in collaboration with National Chung Cheng University (CCU), Taiwan has come out with a Smart Pandemic Prevention Technology. The Taiwan-India Joint Collaboration Effort has been made on alleviating the effects of the ensuing global pandemic problem.

CCU and SRMIST have shared smart and advanced technologies resulting in the implementation and deployment of the Smart Pandemic Prevention System (SPPS) which includes smart face recognition, thermal body temperature monitoring and real-time social contact analysis.

A presentation of the results of the “Taiwan-India Joint Collaboration in Smart Pandemic Prevention System” was held online, presided by Vice Chancellor (Interim) of SRMIST Dr C Muthamizchelvan and Pro-Vice Chancellor (Medical and Health Science) of SRMIST Lt Col Dr A Ravi Kumar along with Dr Mu-Min Chen, Deputy Representative of TECC, Dr CT Wang, Director of Science and Technology, TECC, Dr Chadaram Sivaji, Director of International Bilateral Cooperation Division, DST, India.

The Taipei Economic and Cultural Center (TECC) and Taiwan Education Center (TEC) had invited the Taiwan-India Joint Research Center on Artificial Intelligence organised by the National Chung Cheng University (CCU) and IIT Ropar along with the SRMIST to jointly create a Smart Pandemic Prevention System (SPPS) which is currently deployed on the campuses of both CCU and SRMIST, with the possibility of extending it to hospitals and other hotspot areas where pandemic prevention is of utmost importance.

The system has four main features, including automatic body monitoring and recording, smart face recognition, along with face mask recognition and social contact analysis. Automatic body monitoring was achieved using a thermal camera, but the students and professors worked on making the software checking more accurate. This helped reduce the number of employees that were needed for checking body temperatures at each and every entrance/exit on campus.

Face recognition adapted the latest deep neural network model such as MTCNN and MobileFacenet, with optimisations for Indian faces. Face tracking was achieved using the SORT algorithm. An edge-based version was also developed on the Nvidia Jetson Nano board.