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. C. T. 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 organized 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 hot-spot areas where pandemic prevention is of utmost importance.
The Taiwan-India Smart Pandemic Prevention System has four main features, including automatic body monitoring and recording, smart face recognition, along with face mask recognition, and social contact analysis. Not only did the students of CCU and SRMIST work together in the latest AI technology, but also actually the system on both campuses, benefiting the employees of both universities with safe entrance/exit control. 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 optimizations for Indian faces. Face tracking was achieved using the SORT algorithm. An edge-based version was also developed on the Nvidia Jetson Nano board.
Given the data from the body monitoring and face recognition, social contact analysis was performed for site-specific, as well as, person-specific. Most systems deployed worldwide require mobile phone data for tracking. Our system did not require such data and effectively analyzed the social contacts in specifically monitored areas. The above-described three features of the smart pandemic prevention system helped not only the people on the two campuses, but also helped corroborate the relations between Taiwan and India.