Abstract
The global spread of COVID-19 is a growing concern for everyone. The virus is transmitted through droplets and airborne particles from one person to another. The World Health Organization (WHO) recommends wearing a face mask, social distancing, avoiding crowded areas, and maintaining a strong immune system to reduce the spread of COVID-19. In response to the pandemic, many countries have implemented lockdowns to control its spread. Research has shown that wearing masks in public can help prevent person-to-person transmission of the virus. This paper proposes a device that uses cameras to detect elevated body temperature, people wearing face masks, those not wearing face masks, and calculates proximity among individuals. The proposed model can be deployed in public places such as shopping malls, hotels, apartment entrances, airports, hospitals, and offices to maintain safety standards. The system uses Internet of Things (IoT) technology and deep learning mechanisms to detect individuals who may be infected with COVID-19. The proposed framework is evaluated using the face mask detection and social distance detecting algorithms in the TensorFlow library. A non-contact sensor is used to check the temperature of each person passing through the device. To ensure ease of use, an animated film is used to help people understand how to operate the proposed system. A multimedia application is also employed to display the system’s output to end-users in the form of visualizations or reports, accompanied by an alarming sound to remind individuals to maintain distance or avoid crowded areas. The proposed system, when implemented, can help prevent the spread of COVID-19 and save lives.
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References
Chan JF-W, To KK-W, Tse H et al (2013) Interspecies transmission and emergence of novel viruses: lessons from bats and birds. Trends Microbiol 21(10):544–555
Ng DK-k, Chan C-h, Chan EY-t, Kwok K-l, Chow P-y, Lau W-F, Ho JC-S (2005) A brief report on the normal range of forehead temperature as determined by noncontact, handheld, infrared thermometer. Am J Infect Control 33(4):227–229. https://doi.org/10.1016/j.ajic.2005.01.003. PMID: 15877017; PMCID: PMC7115295
Kumar S, Gupta SK, Kaur M, Gupta U (2022) VI-NET: a hybrid deep convolutional neural network using VGG and inception V3 model for copy-move forgery classification. J Vis Commun Image Represent 89:103644
Singh S, Bhardwaj A, Budhiraja I, Gupta U, Gupta I (2023) Cloud-based architecture for effective surveillance and diagnosis of COVID-19. In: Convergence of cloud with AI for big data analytics: foundations and innovation. Scrivener Publishing LLC, pp 69–88
Gupta U, Gupta D (2021) Kernel-target alignment based fuzzy Lagrangian twin bounded support vector machine. Int J Uncertainty Fuzziness Knowl Based Syst 29(5):677–707
Kumar S, Gupta S, Gupta U (2022) Discrete cosine transform features matching-based forgery mask detection for copy-move forged images. In: 2022 2nd international conference on innovative sustainable computational technologies (CISCT). IEEE, pp 1–4
Chen Y, Cheng J, Jiang X, Xu X (2020) The reconstruction and prediction algorithm of the fractional TDD for the local outbreak of COVID-19. arXiv:2002.10302 [physics.soc-ph], arXiv:2002.10302v1 [physics.soc-ph], https://doi.org/10.48550/arXiv.2002.10302
Gupta U, Dutta M, Vadhavaniya M (2013) Analysis of target tracking algorithm in thermal imagery. Int J Comput Appl 71(16):34–41
Long G (2016) Design of a non-contact infrared thermometer. Int J Smart Sens Intell Syst 9(2):1110–1129. https://doi.org/10.21307/ijssis-2017-910
Barnawi A, Chhikara P, Tekchandani R, Kumar N, Alzahrani B (2021) Artificial intelligence-enabled Internet of Things-based system for COVID-19 screening using aerial thermal imaging. Future Gener Comput Syst 124:119–132. https://doi.org/10.1016/j.future.2021.05.019. Epub 2021 May 26. PMID: 34075265; PMCID: PMC8152244
Yugakiruthika AB, Malini A (2022) A comprehensive tool survey for blockchain to IoT applications. In: Data engineering for smart systems: proceedings of SSIC 2021. Springer Singapore, pp 89–99
Yugakiruthika AB, Malini A (2022) Security testing for blockchain enabled IoT system. In: Data engineering for smart systems: proceedings of SSIC 2021. Springer Singapore, pp 45–55
Varshini B, Yogesh HR, Pasha SD, Suhail M, Madhumitha V, Sasi A (2021) IoT-enabled smart doors for monitoring body temperature and face mask detection. Glob Transitions Proc 2(2):246–254. https://doi.org/10.1016/j.gltp.2021.08.071. ISSN 2666–285X
Chavda A, Dsouza J, Badgujar S, Damani A (2021) Multi-stage CNN architecture for face mask detection. In: 2021 6th international conference for convergence in technology (I2CT). IEEE, pp 1–8
Petropoulos F, Makridakis S (2020) Forecasting the novel coronavirus COVID-19. PLoS ONE 15(3):e0231236-1–e0231236-8. https://doi.org/10.1371/journal pone.0231236
Akash V, Sridevi S, Ananthi G, Rajaram S (2021) Forecasting of novel corona virus disease (covid-19) using LSTM and XG boosting algorithms. In: Data analytics in bioinformatics—a machine learning perspective. Wiley Publishers
Retrieved from https://en.wikipedia.org/wiki/Infrared_thermometer
Retrieved from https://serverscheck.com/solutions/corona-covid-19.asp
Retrieved from https://spectrum.ieee.org/why-use-timeofflight-for-distance-measurement
Retrieved from https://www.pyimagesearch.com/2020/05/04/covid-19-face-mask-detector-with-opencv-keras-tensorflow-and-deep-learning/
Retrieved from https://pyimagesearch.com/2018/08/13/opencv-people-counter/
Retrieved from https://pyimagesearch.com/2020/06/01/opencv-social-distancing-detector/
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Moorthy, T.S.D., Nimalan, N., Sridevi, S., Nevetha, B. (2024). Prevention Equipment for COVID-19 Spread Using IoT and Multimedia-Based Solutions. In: Swaroop, A., Polkowski, Z., Correia, S.D., Virdee, B. (eds) Proceedings of Data Analytics and Management. ICDAM 2023. Lecture Notes in Networks and Systems, vol 785. Springer, Singapore. https://doi.org/10.1007/978-981-99-6544-1_9
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DOI: https://doi.org/10.1007/978-981-99-6544-1_9
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