An Optimized Deep Learning Approach for the Prediction of Social Distance Among Individuals in Public Places During Pandemic.

Social distancing is considered as the most effective prevention techniques for combatting pandemic like Covid-19. It is observed in several places where these norms and conditions have been violated by most of the public though the same has been notified by the local government. Hence, till date, there has been no proper structure for monitoring the loyalty of the social-distancing norms by individuals. This research has proposed an optimized deep learning-based model for predicting social distancing at public places. The proposed research has implemented a customized model using detectron2 and intersection over union (IOU) on the input video objects and predicted the proper social-distancing norms continued by individuals. The extensive trials were conducted with popular state-of-the-art object detection model: regions with convolutional neural networks (RCNN) with detectron2 and fast RCNN, RCNN with TWILIO communication platform, YOLOv3 with TL, fast RCNN with YOLO v4, and fast RCNN with YOLO v2. Among all, the proposed (RCNN with detectron2 and fast RCNN) delivers the efficient performance with precision, mean average precision (mAP), total loss (TL) and training time (TT). The outcomes of the proposed model focused on faster R-CNN for social-distancing norms and detectron2 for identifying the human 'person class' towards estimating and evaluating the violation-threat criteria where the threshold (i.e., 0.75) is calculated. The model attained precision at 98% approximately (97.9%) with 87% recall score where intersection over union (IOU) was at 0.5.

A proposal for testing kit of corona viruses using 3D photonic structure.

Design of corona virus testing kit is proposed in this paper using silicon based 3D photonic structure through zirconium quantum dot solution at the signal of 412 nm. The principle of measurement depends on the computation of reflectance, absorbance and transmittance of virus based quantum dot solution. In this paper, the reflectance is studied through the analysis of photonic band gap and absorbance is made through its numerical treatment. Further, the numerical investigation shows that the transmitted energy through photonic structure would determine the type of corona virus. For example; if the transmitted energy lies within the visible spectrum the sample would be normal corona virus. However, the sample could be IBV (SARS COV-2) if the transmitted energy would be Infrared.