Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices
The Covid-19 epidemic has been causing heavy losses to humanity in terms of population, economy, and political stability. To deal with outbreaks of the pandemic, countries have been racing to develop vaccines and issue many regulations for people in daily life. Wearing a facemask in public is mandat...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9732460/ |
| _version_ | 1830230534145441792 |
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| author | Duy-Linh Nguyen Muhamad Dwisnanto Putro Kang-Hyun Jo |
| author_facet | Duy-Linh Nguyen Muhamad Dwisnanto Putro Kang-Hyun Jo |
| author_sort | Duy-Linh Nguyen |
| collection | DOAJ |
| description | The Covid-19 epidemic has been causing heavy losses to humanity in terms of population, economy, and political stability. To deal with outbreaks of the pandemic, countries have been racing to develop vaccines and issue many regulations for people in daily life. Wearing a facemask in public is mandatory and will be severely punished if violated. In addition to the above mandatory regulations, it is necessary to develop tools for early warning when the human does not wear the facemask in public places such as offices, schools, supermarkets, train stations, etc. This paper proposed a facemask wearing alert system based on a simple convolutional neural network (CNN) operating on low-computing devices. This system works in two stages: face detection and facemask classification. In the first stage, it uses a face detection network with the main benefit of convolution, separable depthwise convolution, and double detectors layer to extract face region of interest (RoI). Then, this image area will go through a facemask classification network that exploits the advantages of convolution, separable depthwise convolution, and skip connection layers to classify facemask wearing (Mask or NoMask). The proposed networks are trained and evaluated on benchmark datasets. Along with simple designs, optimizing network parameters without ignoring accuracy, the system works in real-time at 33.17 and 26.18 frames per second (FPS) on an Intel Core I7-4770 CPU @ 3.40 GHz (Personal Computer - PC) and a Nvidia Maxwell GPU (Jetson Nano device), respectively. The demo video can be found here <uri>https://bit.ly/3yUgb8f</uri>. |
| first_indexed | 2024-12-18T10:55:01Z |
| format | Article |
| id | doaj.art-d1b2e17831e342d29220900e477a7aa6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-18T10:55:01Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d1b2e17831e342d29220900e477a7aa62022-12-21T21:10:21ZengIEEEIEEE Access2169-35362022-01-0110299722998110.1109/ACCESS.2022.31583049732460Facemask Wearing Alert System Based on Simple Architecture With Low-Computing DevicesDuy-Linh Nguyen0https://orcid.org/0000-0001-6184-4133Muhamad Dwisnanto Putro1Kang-Hyun Jo2https://orcid.org/0000-0002-4937-7082Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan, South KoreaDepartment of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan, South KoreaDepartment of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan, South KoreaThe Covid-19 epidemic has been causing heavy losses to humanity in terms of population, economy, and political stability. To deal with outbreaks of the pandemic, countries have been racing to develop vaccines and issue many regulations for people in daily life. Wearing a facemask in public is mandatory and will be severely punished if violated. In addition to the above mandatory regulations, it is necessary to develop tools for early warning when the human does not wear the facemask in public places such as offices, schools, supermarkets, train stations, etc. This paper proposed a facemask wearing alert system based on a simple convolutional neural network (CNN) operating on low-computing devices. This system works in two stages: face detection and facemask classification. In the first stage, it uses a face detection network with the main benefit of convolution, separable depthwise convolution, and double detectors layer to extract face region of interest (RoI). Then, this image area will go through a facemask classification network that exploits the advantages of convolution, separable depthwise convolution, and skip connection layers to classify facemask wearing (Mask or NoMask). The proposed networks are trained and evaluated on benchmark datasets. Along with simple designs, optimizing network parameters without ignoring accuracy, the system works in real-time at 33.17 and 26.18 frames per second (FPS) on an Intel Core I7-4770 CPU @ 3.40 GHz (Personal Computer - PC) and a Nvidia Maxwell GPU (Jetson Nano device), respectively. The demo video can be found here <uri>https://bit.ly/3yUgb8f</uri>.https://ieeexplore.ieee.org/document/9732460/Convolutional neural networkCovid-19low-computing devicesfacemask wearing alert system |
| spellingShingle | Duy-Linh Nguyen Muhamad Dwisnanto Putro Kang-Hyun Jo Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices IEEE Access Convolutional neural network Covid-19 low-computing devices facemask wearing alert system |
| title | Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices |
| title_full | Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices |
| title_fullStr | Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices |
| title_full_unstemmed | Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices |
| title_short | Facemask Wearing Alert System Based on Simple Architecture With Low-Computing Devices |
| title_sort | facemask wearing alert system based on simple architecture with low computing devices |
| topic | Convolutional neural network Covid-19 low-computing devices facemask wearing alert system |
| url | https://ieeexplore.ieee.org/document/9732460/ |
| work_keys_str_mv | AT duylinhnguyen facemaskwearingalertsystembasedonsimplearchitecturewithlowcomputingdevices AT muhamaddwisnantoputro facemaskwearingalertsystembasedonsimplearchitecturewithlowcomputingdevices AT kanghyunjo facemaskwearingalertsystembasedonsimplearchitecturewithlowcomputingdevices |