A Deep Learning Based Social Distance Analyzer with Person Detection and Tracking Using Region Based Convolutional Neural Networks for Novel Coronavirus
DOI:
https://doi.org/10.13052/jmm1550-4646.1834Keywords:
Convolutional Neural Network (CNN), YOLO V3, Region-Based Convolutional Neural Network (RCNN), CCTV cameras, Drones, novel coronavirusAbstract
With its staggering spread, the continuous novel coronavirus Covid flare-up has caused a worldwide disaster. Populace weakness develops because of an absence of productive helpful prescriptions and a shortage of antibodies against the infection. Since there are no antibodies accessible as of now, social detachment is viewed as a sufficient insurance (standard) against the transmission of the illness. With the ascent in cases, the public authority has ordered a base actual division of 2 meters in all open spaces as a security measure. Utilizing PC vision on video reconnaissance, we made an AI device to forestall the spread of the (novel coronavirus). A social separating analyzer AI apparatus that utilizes video observing from CCTV cameras and robots to control social removing convention. The made AI device was introduced in broad daylight spaces and guaranteed the distance between gatherings of individuals. If the hole was excessively close, the red line showed up, demonstrating a higher danger of being influenced, trailed by the green and yellow light, showing a protected line, and the other, demonstrating a generally safe of being influenced.
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