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Home > Archives > Volume 20, No 8 (2022) > Article

DOI: 10.14704/nq.2022.20.8.NQ44399

Intelligent System for Social Distance Monitoring with Human Detection and Tracking using YOLOv3

Dhanya G Nair, Dr.K.P.Sanal Kumar, Dr.S.Anu H Nair

Abstract

Everyday life and the global economy have been negatively impacted by COVID-19 (Coronavirus). Slowing the spread of coronaviruses through social distance is proven to be an effective strategy in the war against COVID-19. The social distancing is the best way to stop the spread of COVID-19, as it prevents people from coming into intimate touch with each other. Recently, due to the fast spreading outbreak of the COVID-19, one of the obligatory preventive measures to avoid physical contact has become social distance. Surveillance methods that use Deep Learning, Open-CV and Computer vision to follow pedestrians and prevent congestion are the focus of this article. Closed-circuit television (CCTV) and drones can be used for implementation, where the camera will use object detection to identify the crowd and compute the distance between the humans. Local law enforcement will be notified if the Euclidean distance between two persons is less than the standard distance, which is determined by converting it to pixels and comparing it to that value

Keywords

Deep learning ,CCTV, Open CV, Social distancing, , Computer vision.

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