Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Social distancing measures are necessary for many infectious diseases that spreads through droplets and microdroplets. According to WHO, the preventive measure for COVID-19 is to follow strict social distancing. It is not easy to enforce social distance easily in a crowded region and people often not maintain sufficient distance with neighbours. Driven by the need for energy-efficient and cost-effective social distancing monitoring, this paper proposes Smart Social Distancing (SSD) mobile application based monitoring, which can predict the social distancing between two people assisted by mobile bluetooth and mobile camera. SSD involves two major steps to predict the social distance: first the pedestrian in the video frames is identified with the aid of Deep Learning (DL) and in the second step, distance between the two pedestrian is estimated through image processing techniques. The application can also be configured to calculate the distance using Bluetooth Low Energy (BLE) by calculating its received signal strength. The application demonstrates 85% accuracy on predicting the social distancing and alert the user using beep sound or alert message.
Dr. Neelavathy Pari S. 2020. \u201cMonitoring Social Distancing by Smart Phone App in the effect of COVID-19\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 20 (GJCST Volume 20 Issue C2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 108
Country: India
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: Dr. Neelavathy Pari S, Balaji Vasu, Geetha A V (PhD/Dr. count: 1)
View Count (all-time): 246
Total Views (Real + Logic): 3899
Total Downloads (simulated): 1005
Publish Date: 2020 12, Mon
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Social distancing measures are necessary for many infectious diseases that spreads through droplets and microdroplets. According to WHO, the preventive measure for COVID-19 is to follow strict social distancing. It is not easy to enforce social distance easily in a crowded region and people often not maintain sufficient distance with neighbours. Driven by the need for energy-efficient and cost-effective social distancing monitoring, this paper proposes Smart Social Distancing (SSD) mobile application based monitoring, which can predict the social distancing between two people assisted by mobile bluetooth and mobile camera. SSD involves two major steps to predict the social distance: first the pedestrian in the video frames is identified with the aid of Deep Learning (DL) and in the second step, distance between the two pedestrian is estimated through image processing techniques. The application can also be configured to calculate the distance using Bluetooth Low Energy (BLE) by calculating its received signal strength. The application demonstrates 85% accuracy on predicting the social distancing and alert the user using beep sound or alert message.
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