Open AccessSmart System to Monitor Social-Distancing During the Covid-19 Pandemic
Author(s) -
Omar Elharrouss,
Noor Almaadeed,
Khalid Abualsaud,
Ahmed Adel Mahmoud,
Tamer Khattab,
Somaya AlMaadeed,
Ali Alali
Publication year - 2020
Publication title -
university of the future: re-imagining research and higher education
Language(s) - English
Resource type - Conference proceedings
DOI - 10.29117/quarfe.2020.0297
Subject(s) - social distance , computer science , computer vision , task (project management) , artificial intelligence , visualization , tracking system , real time computing , covid-19 , infectious disease (medical specialty) , engineering , kalman filter , medicine , disease , systems engineering , pathology
We introduce a smart system to track and maintain real-time physical distance between people and to warn people over any deviation from the prescribed distances. Social-distancing is an effective way of slowing infectious disease spread. People are advised to reduce their contacts with each other, thus reducing the chances of transmitting the disease through physical or near contact. We proposed a system to automate the task of tracking social distance using video surveillance and sensors. The system can be used to detect moving objects and measure distance between people. The system collected sensor environmental information for commercial, industrial and governmental purposes. Furthermore we are using drown to detect crowded area. The accuracy of detection using sensors can be helpful when it combined with the camera for computer vision task in terms of visualization using camera and rebuses of detection using sensor. Both camera and sensor gauge the environment to detect moving objects simultaneously.