Abstract
Over 3 years, we are living under various restrictions due to the covid’19 pandemic. First, was the lockdown, then authorities allow people to go outside for a very limited duration. Second, the obligation of wearing a facemask to protect ourselves and others. Third, after being vaccinated with three shots, everyone has a vaccination passport or some call it a Health pass. This pass allows people to go whatever they want and to travel outside the country. We build a complete application able to manage and monitor: 1/ Social Distance, 2/ Facemask detection, and 3/ check the vaccination passport. We use deep learning models to do classification and detection. The resulting application is very flexible and user-friendly. Also, it could be used anywhere; schools, universities, public spaces, private buildings, etc. We tested our application with various devices including Raspberry Pi, wireless camera, and laptop.
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References
Researchers use Oura smart rings to predict onset of COVID-19 symptoms | Engadget. https://www.engadget.com/wvu-oura-smart-ring-coronavirus-study-162058734.html. Accessed 04 Apr 2022
Phelan, D.: Apple Watch Can Detect Covid-19 Before Symptoms Arise, New Study Shows. https://www.forbes.com/sites/davidphelan/2021/01/17/apple-watch-can-detect-covid-19-before-symptoms-arise-new-study-shows/. Accessed 04 Apr 2022
Apple releases new COVID-19 app and website based on CDC guidance. https://www.apple.com/newsroom/2020/03/apple-releases-new-covid-19-app-and-website-based-on-CDC-guidance/. Accessed 04 Apr 2022
Nv, R.K., Arun, M., Baraneetharan, E., Stanly Jaya Prakash, J., Kanchana, A., Prabu, S.: Detection and monitoring of the asymptotic COVID-19 patients using IoT devices and sensors. Int. J. Pervas. Comput. Commun. (2020). https://doi.org/10.1108/IJPCC-08-2020-0107
Hosny, K.M., Darwish, M.M., Li, K., Salah, A.: COVID-19 diagnosis from CT scans and chest X-ray images using low-cost Raspberry Pi. PLoS ONE 16, e0250688 (2021). https://doi.org/10.1371/journal.pone.0250688
Barabas, J., Zalman, R., Kochlan, M.: Automated evaluation of COVID-19 risk factors coupled with real-time, indoor, personal localization data for potential disease identification, prevention and smart quarantining. In: 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), pp. 645–648 (2020). https://doi.org/10.1109/TSP49548.2020.9163461
ben Abdel Ouahab, I., Elaachak, L., Bouhorma, M., Alluhaidan, Y.A.: Real-time facemask detector using deep learning and raspberry pi. In: 2021 International Conference on Digital Age Technological Advances for Sustainable Development (ICDATA), pp. 23–30 (2021). https://doi.org/10.1109/ICDATA52997.2021.00014
Chappidi, S., Nag, K., Shukla, D., Jindal, S.K.: New COVID-19 normal: An experimental prototype of smart face mask vending machine—An indispensable kiosk. In: Sikdar, B., Prasad Maity, S., Samanta, J., and Roy, A. (eds.) Proceedings of the 3rd International Conference on Communication, Devices and Computing, pp. 125–133. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-9154-6_13
Teach, Learn, and Make with Raspberry Pi – Raspberry Pi. https://www.raspberrypi.org/
Intel® Neural Compute Stick 2. https://www.intel.com/content/www/us/en/develop/hardware/neural-compute-stick.html, last Accessed 25 Sept 2020
Redmon, J., Farhadi, A.: YOLOv3: An Incremental Improvement. arXiv:1804.02767 [cs] (2018)
Lin, T.-Y., et al.: Microsoft COCO: Common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740–755. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10602-1_48
Ben abdel ouahab, I., Elaachak, L., Elouaai, F., Bouhorma, M.: A smart surveillance prototype ensures the respect of social distance during COVID19. In: Ben Ahmed, M., Rakıp Karaș, İ, Santos, D., Sergeyeva, O., Boudhir, A.A. (eds.) SCA 2020. LNNS, vol. 183, pp. 1197–1209. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-66840-2_91
CDC: COVID-19 and Your Health. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html. Accessed 31 Jan 2022
Ben Abdel Ouahab, I.: SocialDistanceSSDRaspberry (2022)
Ben Abdel Ouahab, I.: SocialDistanceYOLORaspberry (2022)
Kwan, R.Y.C., Lee, P.H., Cheung, D.S.K., Lam, S.C.: Face mask wearing behaviors, depressive symptoms, and health beliefs among older people during the COVID-19 pandemic. Front. Med. 8 (2021)
Acknowledgements
This project is subsidized by the MENFPESRS and the CNRST as part of the program to support scientific and technological research related to “COVID-19” (2020). Also, we acknowledge the financial support for this research from CNRST.
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Ben Abdel Ouahab, I., Elaachak, L., Elouaai, F., Bouhorma, M. (2023). Application of AI and IoT in the Containment of the Covid19 Pandemic. In: Ben Ahmed, M., Boudhir, A.A., Santos, D., Dionisio, R., Benaya, N. (eds) Innovations in Smart Cities Applications Volume 6. SCA 2022. Lecture Notes in Networks and Systems, vol 629. Springer, Cham. https://doi.org/10.1007/978-3-031-26852-6_65
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