Monitoring Social Distancing by Smart Phone App in the effect of COVID-19

Dr. Neelavathy Pari S; Balaji Vasu; Geetha A V

Monitoring Social Distancing by Smart Phone App in the effect of COVID-19

Dr. Neelavathy Pari S * §

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Balaji Vasu

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Geetha A V

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Anna University

Monitoring Social Distancing by Smart Phone App in the effect of COVID-19

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Abstract

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.

References

7 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. S, Balaji Vasu, Geetha V. 2020. "Monitoring Social Distancing by Smart Phone App in the effect of COVID-19". Global Journal of Computer Science and Technology, Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 20 (GJCST Volume 20 Issue C2).

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GJCST Volume 20 Issue C2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-C Classification H.4.0

Submission ReceivedDecember 12, 2019
Peer Review Double Blind
Handling Editor
Accepted January 4, 2020
Published January 15, 2020

Version of record

v1.2

Issue date

December 21, 2020

Language

English

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