A Safety Measuring Tool to Maintain Social Distancing On COVID-19 Using Deep Learning Approach

Abstract

Due to this recent wave of the Deadly corona virus disease, which has spread widely all over the world, so physical or Social distancing has become a mandatory precaution to avoid close contact. As of January 2021, the count of affected cases is 10.8 million and recovered cases are 10.5 million and the death rate is 155 thousand. In conformity, we have proposed a system that elucidates the usage of Python, computer vision, and deep learning to monitor whether people are maintaining Social distance at public areas in roads, pathways, work places and, even in hospitals. For the purpose of monitoring social distances among people, we have developed a social distancing detection tool that can keep track of safe distance and determine the distance between people in order to reduce the impact of the corona virus pandemic by analyzing real-time video Streaming, such as CCTV or Camera which can be added with the security camera system at hospitals, workplaces, markets, Jewelers shop etc. As an output, the detection tool will throw A Voice alert or a Notification, so that people would be remained to maintain a social distance.

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

“…Deep learning and machine learning-based AI models surpass various criteria such as time consumption and labor intensive where human interventions are must in research and also to obtain results/outcomes that have minimal errors and loss with alternate predictions by shortening the period of investigations from years, months and days into several days [ 8 ]. Majorly R-CNN (region-based CNN) and faster R-CNN are utilized for accurate and faster predictions.…”

Social Distance Approximation on Public Transport Using Stereo Depth Camera and Passenger Pose Estimation

“…Pose estimation can also be utilised to enhance scene restoration with this approach, allowing for auto-calibration techniques before social distance measurement [ 14 ]. Several methodologies are successful in detecting people but fail to perform any mapping between the image plane and object world—instead relying on apparent arbitrary threshold values [ 15 ], simple Euclidean distances between two image pixel points [ 16 ], or scale based on highly unreliable detected bounding box sizes in relation to expected human dimensions [ 17 , 18 ].…”

An Empirical Study of Post Covid19 Pandemic on Micro and Small Enterprises (MSEs) of Telework

“…The bright part of telework explained by Pooranam et al (2021); Ruth & Chaudhry (2008), generally, employees have a more optimistic approach as they report more significant levels of job satisfaction and fulfillment of tasks and do a better job while telework. Similarly, the pandemic has reshaped the routine work environment and make bosses reconsider how fundamental responsibilities should be possible, which might broaden their perspectives on working environment facilities and may provide equal opportunities to disable and single mother.…”

“…Telework ensures that essential functions continue during emergency situations also Fraij & Aburumman (2021) briefs that telework is consistently a possibility for governments and organizations. This practice turned out to be substantially more standard during the COVID-19 as everyone need to keep a decent distance among yourself as well as other people, when a huge number of laborers had to begin remote working on urgent basis pandemic (Pooranam et al, 2021).…”