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Social distancing monitoring system using deep learning

Ismail, Amelia Ritahani and Muhd Affendy, Nur Shairah and Ismail, Ahsiah and Ahmad Puzi, Asmarani (2022) Social distancing monitoring system using deep learning. Knowledge Engineering and Data Science (KEDS), 5 (1). pp. 17-26. ISSN 2597-4602 E-ISSN 2597-4637

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COVID-19 has been declared a pandemic in the world by 2020. One way to prevent COVID-19 disease, as the World Health Organization (WHO) suggests, is to keep a distance from other people. It is advised to stay at least 1 meter away from others, even if they do not appear to be sick. The reason is that people can also be the virus carrier without having any symptoms. Thus, many countries have enforced the rules of social distancing in their Standard Operating Procedure (SOP) to prevent the virus spread. Monitoring the social distance is challenging as this requires authorities to carefully observe the social distancing of every single person in a surrounding, especially in crowded places. Real-time object detection can be proposed to improve the efficiency in monitoring the social distance SOP inspection. Therefore, in this paper, object detection using a deep neural network is proposed to help the authorities monitor social distancing even in crowded places. The proposed system uses the You Only Look Once (YOLO) v4 object detection models for the detection. The proposed system is tested on the MS COCO image dataset with a total of 330,000 images. The performance of mean average precision (mAP) accuracy and frame per second (FPS) of the proposed object detection is compared with Faster Region-based Convolutional Neural Network (R-CNN) and Multibox Single Shot Detector (SSD) model. Finally, the result is analyzed among all the models.

Item Type: Article (Journal)
Uncontrolled Keywords: Deep learning, Object detection, Social distancing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Amelia Ritahani Ismail
Date Deposited: 22 Nov 2022 11:00
Last Modified: 22 Nov 2022 11:00
URI: http://irep.iium.edu.my/id/eprint/101344

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