A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications
Facial mask detection technology has become increasingly important even beyond the context of the COVID-19 pandemic. Along with the advancement in facial recognition technology, face mask detection has become a crucial feature for various applications. This paper introduces an Internet of Things (Io...
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MDPI AG
2023-07-01
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| Online Access: | https://www.mdpi.com/2078-2489/14/7/379 |
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| author | Viet Q. Vu Minh-Quang Tran Mohammed Amer Mahesh Khatiwada Sherif S. M. Ghoneim Mahmoud Elsisi |
| author_facet | Viet Q. Vu Minh-Quang Tran Mohammed Amer Mahesh Khatiwada Sherif S. M. Ghoneim Mahmoud Elsisi |
| author_sort | Viet Q. Vu |
| collection | DOAJ |
| description | Facial mask detection technology has become increasingly important even beyond the context of the COVID-19 pandemic. Along with the advancement in facial recognition technology, face mask detection has become a crucial feature for various applications. This paper introduces an Internet of Things (IoT) architecture based on a developed deep learning algorithm named You Only Look Once (YOLO) to keep society healthy, and secured, and collect data for future research. The proposed paradigm is built on the basis of economic consideration and is easy to implement. Yet, the used YOLOv4-tiny is one of the fastest object detection models to exist. A mask detection camera (MaskCam) that leverages the computing power of NVIDIA’s Jetson Nano edge nanodevices was built side by side with a smart camera application to detect a mask on the face of an individual. MaskCam distinguishes between mask wearers, those who are not wearing masks, and those who are not wearing masks properly according to MQTT protocol. Furthermore, a self-developed web browsing application comes with the MaskCam system to collect and visualize statistics for qualitative and quantitative analysis. The practical results demonstrate the superiority and effectiveness of the proposed smart mask detection system. On the one hand, YOLOv4-full obtained the best results even at smaller resolutions, although the frame rate is too small for real-time use. On the other hand, it is twice as fast as the other detection models, regardless of the quality of detection. Consequently, inferences may be run more frequently over the entire video sequence, resulting in more accurate output. |
| first_indexed | 2024-03-11T00:58:28Z |
| format | Article |
| id | doaj.art-3030de7aa14f46d3a0e2b15f16eeb40a |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-11T00:58:28Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-3030de7aa14f46d3a0e2b15f16eeb40a2023-11-18T19:46:48ZengMDPI AGInformation2078-24892023-07-0114737910.3390/info14070379A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security ApplicationsViet Q. Vu0Minh-Quang Tran1Mohammed Amer2Mahesh Khatiwada3Sherif S. M. Ghoneim4Mahmoud Elsisi5Faculty of International Training, Thai Nguyen University of Technology, 3/2 Street, Tich Luong Ward, Thai Nguyen 250000, VietnamDepartment of Mechanical Engineering, TUETECH University, 1B Street Dong Bam Ward, Thai Nguyen 250000, VietnamDepartment of Mechanical Engineering, Palestine Technical University—Kadoorie, Tulkarm P.O. Box 7, PalestineDepartment of Mechanical Engineering, National Yang-Ming Chiao Tung University, Hsinchu 30010, TaiwanDepartment of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi ArabiaDepartment of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 807618, TaiwanFacial mask detection technology has become increasingly important even beyond the context of the COVID-19 pandemic. Along with the advancement in facial recognition technology, face mask detection has become a crucial feature for various applications. This paper introduces an Internet of Things (IoT) architecture based on a developed deep learning algorithm named You Only Look Once (YOLO) to keep society healthy, and secured, and collect data for future research. The proposed paradigm is built on the basis of economic consideration and is easy to implement. Yet, the used YOLOv4-tiny is one of the fastest object detection models to exist. A mask detection camera (MaskCam) that leverages the computing power of NVIDIA’s Jetson Nano edge nanodevices was built side by side with a smart camera application to detect a mask on the face of an individual. MaskCam distinguishes between mask wearers, those who are not wearing masks, and those who are not wearing masks properly according to MQTT protocol. Furthermore, a self-developed web browsing application comes with the MaskCam system to collect and visualize statistics for qualitative and quantitative analysis. The practical results demonstrate the superiority and effectiveness of the proposed smart mask detection system. On the one hand, YOLOv4-full obtained the best results even at smaller resolutions, although the frame rate is too small for real-time use. On the other hand, it is twice as fast as the other detection models, regardless of the quality of detection. Consequently, inferences may be run more frequently over the entire video sequence, resulting in more accurate output.https://www.mdpi.com/2078-2489/14/7/379pandemicmask detectionYOLOdeep learningIoT |
| spellingShingle | Viet Q. Vu Minh-Quang Tran Mohammed Amer Mahesh Khatiwada Sherif S. M. Ghoneim Mahmoud Elsisi A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications Information pandemic mask detection YOLO deep learning IoT |
| title | A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications |
| title_full | A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications |
| title_fullStr | A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications |
| title_full_unstemmed | A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications |
| title_short | A Practical Hybrid IoT Architecture with Deep Learning Technique for Healthcare and Security Applications |
| title_sort | practical hybrid iot architecture with deep learning technique for healthcare and security applications |
| topic | pandemic mask detection YOLO deep learning IoT |
| url | https://www.mdpi.com/2078-2489/14/7/379 |
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