Monitoring Suspects of COVID-19 in Compact Residential Area Using Machine Learning Based on Lockdown Analytical Impact

ABSTRACT

The most prominent symptom in corona-infected person is increased body temperature. Population in India is very high, and it is very difficult to provide medical services to everyone at a time. This paper presents how can we reduce the pressure on medical service providers in current pandemic situation and stop the community spreading. Initially in the paper, impact of lockdown on COVID-19 situation is observed using the Python language. According to that two lockdown applied in the country at initial level, the growth rate of pandemic was under control. But as the lockdown rules were relaxed, quick hike in corona cases was noted. On the basis of this result proposed model is designed, if one scans the temperature of different domain areas at regular intervals from above the surface using zero touch technology, i.e., drone camera installed with thermal sensor, the increased temperature reading can help screening the infected hot spots. The proposed idea is to collect thermal data through thermal sensors and process these data using visualization of images/videos and quantitative methods. Machine learning and artificial intelligence are used to process biometric features of corona suspects and collect personal detail of corona suspect from the databases. The residential area of infected person is marked with red color, and monitoring the movement of the infected person is done with help of machine learning. With the taken of timely action, not only the spreading can be controlled but also the patients can get appropriate attention and treatment on time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.