International Journal of Electronics and Computer Applications

Volume: 1 Issue: 1

  • Open Access
  • Original Article

Precautionary Screening for Covid-19

Meghana Deshpande1 , Pratima Chavan1, Rupali Kamathe1, Kalyani Joshi1, Shraddha Ankolekar1, Kahini Bhusari1, Akshada Bhagat1

1 PES’S Modern College of Engineering, Pune, Maharashtra, India

*Corresponding author email: [email protected]. in

Year: 2024, Page: 11-14,

Received: Feb. 9, 2024 Accepted: April 27, 2024 Published: May 18, 2024

Abstract

The Internet of Things (IoT) is a field that has been utilized to enable remote monitoring and control of home appliances. Automated system is required to develop to save a life of every individual and to stop spread of disease. In this paper real time implementation of face mask and temperature detection system implemented using Raspberry Pi 3 along with some additional features such as servo motor controlled door opening. For face mask recognition, deep leaning methodology used. The Convolution Neural Network is used for detection of face mask. If a face mask is worn and the temperature is below the designated threshold, the door will be unlocked. Conversely, if a face mask is not worn or the temperature exceeds the threshold, a buzzer will sound. The proposed system successfully achieves the results for precision 98% and recalls 99% values.

Keywords: Precautionary Screening for Covid-19

References

  1. MMD. Intelligent Video Surveillance System based on Wavelet Transform and Support Vector MachineInternational Journal of Scientific Development and Research. 2022;7:401–404. Available from: https://doi.org/10.5120/7419-0453

  2. Shinde M, Sukhadare T, Vaidya S, Kalyankar M. Face Mask Detection Alert System using Raspberry PiInternational Research Journal of Engineering and Technology. 2021;08:3020–3022. Available from: https://www.irjet.net/archives/V8/i4/IRJET-V8I4560.pdf

  3. Balachandar V. COVID-19: emerging protective measures”European Review for Medical and Pharmacological Sciences. 2020;24:3422–3425. Available from: https://doi.org/10.26355/eurrev_202003_20713

  4. Ndiaye M, Oyewobi SS, Abu-Mahfouz AM, Hancke GP, Kurien AM, Djouani K. IoT in the Wake of COVID-19: A Survey on Contributions, Challenges and EvolutionIEEE Access. 2020;8:186821–186839. Available from: https://doi.org/10.1109/ACCESS.2020.3030090

  5. Pramila J, Shewta P. Wireless Temperature detector System using ARDUINO and IOTInternational Journal of Computer Trends and Technology. 2019;67:82–83. Available from: https://doi.org/10.14445/22312803/IJCTT-V67I11P113

  6. Viola P, Jones M. Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001. (pp. 1-9) IEEE Comput. Soc. 2001.

Cite this article

Deshpande M, Chavan P, Kamathe R, Joshi K, Ankolekar S, Bhusari K, Bhagat A. (2024). Precautionary Screening for Covid-19. International Journal of Electronics and Computer Applications. 1(1): 11-14.

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