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المؤلفElharrouss, Omar
المؤلفAl-Maadeed, Noor
المؤلفAbualsaud, Khalid
المؤلفMahmoud, Amr
المؤلفKhattab, Tamer
المؤلفAl-Maadeed, Somaya
المؤلفAl-Ali, Ali
تاريخ الإتاحة2020-10-22T06:07:19Z
تاريخ النشر2020
اسم المنشورQatar University Annual Research an Exhibition 2020 (quarfe)
معرّف المصادر الموحدhttps://doi.org/10.29117/quarfe.2020.0297
معرّف المصادر الموحدhttp://hdl.handle.net/10576/16521
الملخصWe introduce a smart system to track and maintain real-time physical distance between people and to warn people to 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 term of visualization using camera and rebuses of detection using sensor. Both camera and sensor gauge the environment to detect moving objects simultaneously.
اللغةen
الناشرQatar University Press
الموضوعCOVID-19
Deep Learning
Imaging
Prediction
Face Recognition
العنوانSmart System to Monitor Social-Distancing During the Covid-19 Pandemic
النوعPoster
dc.accessType Open Access


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