Automated Face Mask Detection using Artificial Intelligence and Video Surveillance Management
15th International Conference on Developments in eSystems Engineering, DeSE 2023
; 2023-January:233-236, 2023.
Article
in English
| Scopus | ID: covidwho-2326274
ABSTRACT
Surveillance camera has become an essential, ubiquitous technology in people's daily lives, whether applicable for home surveillance or extended to public workplace detection. The importance of the camera is irreplaceable in terms of the agent for an enclosed system to function correctly. The goal of ubiquitous computing is to keep different devices or technology communicating seamlessly, allowing them to expand to other areas instead of limiting it to one device. However, many research papers have been released on how the camera can aid in the current situation where COVID-19 is still raging worldwide, especially in crowded places. This paper aims to suggest a method by which surveillance cameras on the university campus can automatically detect student face mask status and notify them. Alongside that, this concept of applying a video management system within the university campus will assist in the automation of invigilating the student's daily mask status from the number of embedded surveillance cameras around the campus. © 2023 IEEE.
CCTV; Convolutional Neural Network (CNN); Face Mask Detection; Ubiquitous Computing; Video Surveillance Management System; Convolutional neural networks; Face recognition; Security systems; Convolutional neural network; Face masks; Management systems; Surveillance cameras; Ubiquitous technology; University campus; Video surveillance; Cameras
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
15th International Conference on Developments in eSystems Engineering, DeSE 2023
Year:
2023
Document Type:
Article
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