Social Distancing detection using machine learning

Venkata ravi kiran kolla


With no doubt, the COVID-19 pandemic has put the world to a halt. The world we lived in a few months prior is completely different than what it is now. The virus is spreading quickly and is a danger to the human race. Seeing the necessity of the hour one must always take certain precautions of which one being social distancing. Maintaining social distancing during COVID-19 is a must to ensure a slowdown in the growth rate of new cases. Our manuscript focuses on detecting if the people around are maintaining social distancing or not. Using our own self developed model named SocialdistancingNet-19 for  etecting the frame of a person and displaying labels, they are marked as safe or unsafe if the distance is less than a certain value. This system can be used for monitoring people via video surveillance in CCTV. Our model achieved an accuracy of 92.8 %.


Whig, P., & Ahmad, S. N. (2013a). A novel pseudo-PMOS integrated ISFET device for water quality monitoring. Active and Passive Electronic Components, 2013.

Whig, P., & Ahmad, S. N. (2014a). Development of economical ASIC for PCS for water quality monitoring. Journal of Circuits, Systems and Computers, 23(06), 1450079.

Whig, P., & Ahmad, S. N. (2014c). Simulation of linear dynamic macro model of photo catalytic sensor in SPICE. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering.

Whig, P. (2019a). A Novel Multi-Center and Threshold Ternary Pattern. International Journal of Machine Learning for Sustainable Development, 1(2), 1–10.

Whig, P. (2019d). Exploration of Viral Diseases mortality risk using machine learning. International Journal of Machine Learning for Sustainable Development, 1(1), 11–20.

Whig, P., & Ahmad, S. N. (2011a). On the performance of ISFET-based device for water quality monitoring. Int’l J. of Communications, Network and System Sciences, 4(11), 709.

kolla, V. (2009). LANE DETECTION SYSTEM USING APPLICATION OF MACHINE LEARNING. Transactions on Latest Trends in Health Sector, 1(1). Retrieved from


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