Open Access
Subscription or Fee Access
Need of Face-Mask Detector Model to Tackle COVID-19 Situation in India
Abstract
The COVID - 19 epidemic is affecting everyone whether rich or poor, strong or weak. The use of a mask can surely aid in the control of the spread of the virus. This becomes even more important for a country like India where the total population is above 135+ crores and due to lockdowns and various other reasons, a huge percentage of the population has dipped below the poverty line and health standards of the poor are declining day by day and all these factors are contributing to an uncontrolled outbreak of coronavirus in India. As the government has already mandated the use of masks as a stop-gap measure to control the pandemic but due to the carelessness of the people they can be categorized into 3 groups based on the use of a mask. Specifically, a person who is properly wearing a mask, or is wearing a mask but improperly, or is not wearing a mask at all. By deep learning, we can make a model which detects masks accurately without human-to-human interactions and can help in controlling this corona pandemic. The Face mask detection system algorithm can be used to detect faces in still images as well as live video streaming and can tell whether the mask is worn properly or not. The mask detector model used should be as flexible as possible and on the same hand simple in structure, so that it can be used by a camera monitoring 1 person at a time or by a public CCTV monitoring hundreds of people at a time. Considering mass screening is possible, it may be utilized in congested areas such as transport hubs, bus stops, supermarkets, sidewalks, mall entrances, schools, and campuses. We can ensure that a person wears the face mask correctly and in a proper way and contribute to minimizing the spread of this destructive virus.
References
Tim Morris. Computer Vision and Image Processing. Red Globe Press. 2004.
Luka Daoud, Muhammad Kamran Latif, et al. A fully pipelined FPGA accelerator for scale-invariant feature transform keypoint descriptor matching. Microprocessors and Microsystems. 2020;72:102919.
Steffen E. Eikenberry, Marina Mancuso, et al. To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic. Infectious Disease MASK DETECTOR MODEL CAMERA PERSON GOOD TO GO PROPER USE OF MASK ALARM IMPROPER USE OF MASK NO MASK Modelling. 2020;5:293-308.
Joseph Redmon and Ali Farhadi. YOLO9000: Better, Faster, Stronger. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 21-26 July 2017; Honolulu, HI, USA, New York: IEEE; 2017.
Chen, Zhuxin, Zhifeng Xie, W. Zhang and Xiangmin Xu. “ResNet and Model Fusion for Automatic Spoofing Detection.”2017, INTERSPEECH. 6. Long Wen, Xinyu Li, et al. A transfer convolutional neural network for fault diagnosis based on ResNet-50. Neural Computing and Applications. 2020;32:6111–6124.
Mohamed Loey, Gunasekaran Manogaran, et al. Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection. Sustainable Cities and Society. 2021;65:102600.
Steffen E. Eikenberry, Marina Mancuso, et al. To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic. Infectious Disease Modelling. 2020;5:293-308.
Wei Liu, Dragomir Anguelov, et al. SSD: Single Shot MultiBox Detector. European Conference on Computer Vision. 2016.
Mohamed Loey, Gunasekaran Manogaran, et al. A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic. Measurement. 2021;167:108288.
Amir Masoud Rahmani and Seyedeh Yasaman Hosseini Mirmahaleh. Coronavirus disease (COVID-19) prevention and treatment methods and effective parameters: A systematic literature review. Sustainable Cities and Society. 2021;64:102568.
Chanjuan Sun and Zhiqiang Zhai (John). The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission. Sustainable Cities and Society. 2020;62:102390.
Liu Yang & Hanxin Chen. Fault diagnosis of gearbox based on RBF-PF and particle swarm optimization wavelet neural network. Neural Computing and Applications. 2019;31:4463–4478.
Shen Yin, Steven X. Ding, et al. A review on basic data-driven approaches for industrial process monitoring. IEEE Transactions on Industrial Electronics. 2014;61(11):6418-6428.
Long Wen, Xinyu Li, et al. A new two-level hierarchical diagnosis network based on convolutional neural network. IEEE Transactions on Instrumentation and Measurement. 2020;69(2):330-338.
Xuewu Dai and Zhiwei Gao. From the model, signal to knowledge: a data-driven perspective of fault detection and diagnosis. IEEE Transactions on Industrial Informatics. 2013;9(4):2226-2238.
Xinyu Li, Liang Gao, et al. An Effective Hybrid Genetic Algorithm and Variable Neighborhood Search for Integrated Process Planning and Scheduling in a Packaging Machine Workshop. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2019;49(10):1933-1945.
Jônatas Wehrmann, Gabriel S. Simões, et al. Adult content detection in videos with convolutional and recurrent neural networks. Neurocomputing. 2018;272:432-438.
Hoo-Chang Shin, Holger R Roth, et al. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics, and Transfer Learning. IEEE Trans Med Imaging. 2016;35(5):1285-1298.
Olivier Janssens, Rik Van de Walle, et al. Deep learning for infrared thermal image-based machine health monitoring. IEEE/ASME Transactions on Mechatronics. 2018;23(1):151-159.
Van Tuan Do1, Ui-Pil Chong. Signal model-based fault detection and diagnosis for induction motors using features of vibration signal in the two-dimension domain. Journal of Mechanical Engineering. 2011;57(9):655-666.
Myeongsu Kang and Jong-Myon Kim. Reliable fault diagnosis of multiple induction motor defects using a 2-d representation of Shannon wavelets. IEEE Transactions on Magnetics. 2014;50(10):8201913.
Lu,Yang Wang, et al. Fault diagnosis for rotating machinery: a method based on image processing. PLoS ONE. 2016;11(10):1-22.
Te Han, Dongxiang Jiang, et al. Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery. Journal Indexing & Metrics. 2018;40(8).
C Lessmeier, JK Kimotho, D Zimmer, W Sextro,” A roller bearing fault diagnosis method based on hierarchical entropy and support vector machine. Journal of Mechanical Engineering Science. 2016;230(13). 26. Sunil Chawla, Mamta Mittal, et al. Corona Virus—SARS-CoV-2: an insight to another way of natural disaster. EAI Endorsed Trans Pervasive Health Technol. 2020;20(22):e4.
Chanjuan Sun and Zhiqiang Zhai (John). The Efficacy of Social Distance and Ventilation Effectiveness in Preventing COVID-19 Transmission. Sustainable Cities and Society. 2020;62:102390.
Sun, Chanjuan, and Zhiqiang Zhai, “The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission. Sustainable cities and society. 2020;62:102390.
World Health Organization. Modes of transmission of the virus causing COVID-19: Implications for IPC precaution recommendations [Online]. Available from https://www.who.int/news-room/commentaries/detail/.
World Health Organization. Coronavirus disease (COVID-19) pandemic [Online]. Available from https://www.who.int/emergencies/diseases/novel-coronavirus-2019.
Xiaojian Xie, Yuguo Li, et al. Exhaled droplets due to talking and coughing. Journal of the Royal Society, Interface. 2009;6(6).
Sorour Alotaibi, W. Chakroun, et al. Influence of mixed and displacement air distribution systems' design on concentrations of micro-particles emitted from floor or generated by breathing. Journal of Building Engineering. 2019;26:100855.
Caiqing Yang, Xudong Yang, et al. Person to person droplets transmission characteristics in unidirectional ventilated protective isolation room: The impact of initial droplet size. Building Simulation. 2016;9:597–606.
J Zhang., M Litvinova, & Y. Liang, “Performance evaluation of a novel personalized ventilation–personalized exhaust system for airborne infection control. 2020, Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science.
DOI: https://doi.org/10.37628/ijippr.v7i1.715
Refbacks
- There are currently no refbacks.