Design of Intelligent Automated Quest Control System in the Covid-19 Era

Yahfizham Yahfizham, Irwan Yusti

Abstract


The rapid spread of corona virus disease 2019 (COVID-19), throughout direct of the human-to-human interaction makes the virus massively infect humans in all around the world. Until now, there has not been found the right way of healing it. This study aims to design of the intelligent automated quest control system capable for detecting COVID-19 by the body of temperature. The method approach was taken applied research, beginning with determining of the hardware using the ArduinoTM UNO microcontroller, the MLX90614 infrared thermometer, the TCRT5000 infrared reflective sensor, motor driver L293D, the output was displayed on a Liquid Crystal Display (LCD) screen, interaction control using Roller Limit Switch and instruction using the C programming language with Arduino IDE user interface. The system testing is done by comparing the temperature sensor readings infrared thermometer versus standard thermometer. Based on the results of a limited scale trial of 5 volunteers, an average error of 2.72% was obtained and the system worked well (opening or locking the door) in accordance with the temperature limits that had been set for detecting COVID-19. This research novelty that the simple and inexpensive design of the device system prevented and minimize the spread of COVID-19. The last, limitations of the system not being tested by the experts and large sample.


Keywords


ArduinoTM UNO, MLX90614 thermometer, TCRT5000 reflective sensor, Motor driver L293D

References


[1] F. He, Y. Deng, and W. Li: Coronavirus disease 2019: What we know ?. J. Med. Virol., Vol. 9, pp. 719–725, 2021.

[2] E. Dong, H. Du, and L. Gardner: COVID-19 in real time. Lancet Infect. Dis., Vol, 20, No. 5, pp. 533–534, 2020.

[3] H. A. Rothan and S. N. Byrareddy: The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J. Autoimmun.,Vol. 109, pp. 1-4, 2020.

[4] K. Leung, J. T. Wu, D. Liu, and G. M. Leung: First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: A modelling impact assessment. Lancet, Vol. 395, pp. 1382–1393, 2020.

[5] J. Yang., et al: Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2. Int. Jour of Inf. Dis, Vol. 94, pp. 91–95, 2020.

[6] B. Udugama., et al: Diagnosing COVID-19: the disease and tools for detection. American Chemical Society (ACS)., Vol. 14, No. 4, pp. 3822-3835, 2020.

[7] Tang Y-W., J. E. Schmitz, D. H. Persing., and C. W, Stratton: Laboratory diagnosis of COVID-19: current issues and challenges. J Clin Microbiol., Vol. 58, No. 6, pp. 1–9, 2020.

[8] L. E. Wee., et al: The role of self‑reported olfactory and gustatory dysfunction as a screening criterion for suspected COVID‑19. Oto-Rhino-Laryngology, pp. 20–21, 2020.

[9] C. Baunez., et al: Sub-National Allocation of COVID-19 Tests: An Efficiency Criterion with an Application to Italian Regions. HAL., pp. 1-18, 2020.

[10] D. Das and K. C. S. Umapada: Truncated inception net: COVID‑19 outbreak screening using chest X ‑ rays. Phys. Eng. Sci. Med., pp. 1-10, 2020.

[11] M. Rahimzadeh and A. Attar: A New Modified Deep Convolutional Neural Network For Detecting Covid-19 From X- Ray Images. arxiv., pp. 1-10, 2020.

[12] T. Ozturk, M. Talo, E. Azra, U. Baran, and O. Yildirim: Automated detection of COVID-19 cases using deep neural networks with X-ray images. Computer in Biology and Medicine., Vol. 121, pp. 1-11, 2020.

[13] R. M. Elavarasan and R. Pugazhendhi: A review on potential technological strategies to control the COVID-19 pandemic. Science of the Tot. Env.., Vol, 725, pp. 1-18, 2020.

[14] R. Vaishya, M. Javaid, I. Haleem, and A. Haleem: Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews., Vol. 14, pp. 337-339, 2020.

[15] D. Shu., et al: Digital technology and COVID-19. Nature Medicine., Vol. 26, pp. 2019–2021, 2020.

[16] T. Yang, M. Gentile, C-F. Shen, and C-M. Cheng: Combining Point-of-Care Diagnostics and Internet of Medical Things (IoMT) to Combat the Pandemic. Diagnostics., Vol. 10, pp. 4–6, 2020.

[17] K. C. Santosh: AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data. Journal of Medical System., Vol. 44, No. 93, pp. 1–5, 2020.

[18] F. Shi., et al: Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19. IEEE Review in Biomedical Engineering., pp. 1–11, 2020.

[19] M. E. H. Chowdhury., et al: Can AI help in screening Viral and COVID-19 pneumonia ?. IEEE Access., Vol, XX, pp. 1-12, 2020.

[20] F. M. Salman., et al: COVID-19 Detection using Artificial Intelligence. International Journal of Academic Engineering Research (IJAER)., Vol. 4, No. 3, pp. 18–25, 2020.

[21] I. D. Apostolopoulos and T. A. Mpesiana: Covid‑19: Automatic detection from Xray images utilizing transfer learning with convolutional neural networks. Phys. Eng. Sci. Med., Vol. 43, No. 2, pp. 635–640, 2020.

[22] J. Zhang., et al: Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection. Manuscript., pp. 1–11, 2020.

[23] J. Health, M. Sinai, and K. Permanente: Virtually Perfect ? Telemedicine for Covid-19. The New England Journal of Medicine., Vol. 382, No. 18, pp. 1679–1681, 2020.

[24] S. G. M. Pereira, F. A. S. Medina, and D. S. D. Santos: Software Project for Remote Monitoring of Body Temperature. IEEE Latin America Transactions., Vol. 15, No. 11, pp. 2238–2243, 2017.

[25] F. Yazdani and F. A. Mohammadi: Intelligent testing for Arduino UNO based on thermal image R. Comput. Electr. Eng., Vol. 58, pp. 88–100, 2017.

[26] K. Xie, H. Zhang, L. Ding, and B. Hu. 2014. Design and implementation of shield state detection system for charging pile port. Applied Mechanics and Materials., 556-562, pp. 3027–3030.

[27] A. Al-Yemni: An Arduino based smart faucet design. COMPUSOFT, An international journal of advanced computer technology., Vol. 7, No. 5, 2018, pp. 5–8.

[28] I. Yusti : Pengontrolan Pintu Pagar Otomatis menggunakan Android, Jurnal Sains dan Teknologi., Vol. 21, No. 1, 2021, pp. 97–101.

[29] I. Yusti and A. Bachtiar: Kontrol Lampu Menggunakan Voice Recognizer Berbasis Android, JPTK., Vol. 2, No. 4, 2020, pp. 140–143.

[30] O. V. Vovna., et al: Study of metrological characteristics of low-cost digital temperature sensors for greenhouse conditions, Serbian Journal of Electrical Engineering, Vol. 17, No. 1, pp. 1-20, 2020.

[31] M. Milošević, et al: Lighting control using Raspberry Pi and OBLO living home automation system, Serbian Journal of Electrical Engineering, Vol. 16, No. 1, pp. 45-54, 2019.

[32] U. Jovanović, et al: Low-cost teslameter based on hall effect sensor MLX90242, Serbian Journal of Electrical Engineering, Vol. 15, No. 2, pp. 225-232, 2018.

[33] Y. Li and M. Sun: Generating Arduino C Codes, Springer International Publishing AG, part of Springer Nature., pp. 174–188, 2018.

[34] P. Teikari., et al: An inexpensive Arduino-based LED stimulator system for vision research. J. Neurosci. Methods., Vol. 211, No. 2, pp. 227–236, 2012.

[35] N. Ni, S. Hlaing, and S. S. Lwin: Electronic Door Lock using RFID and Password Based on Arduino. International Journal of Trend in Scientific Research and Development (IJTSRD)., Vol. 3, No. 3, pp. 799–802, 2019.

[36] B. M. Amine, C. F. Zohra, H. Ilyes, A. Lahcen, and A. Tayeb: Smart Home Automation System based on Arduino. International Journal of Robotics and Automation (IJRA)., Vol. 7, No. 4, pp. 215–220, 2018.

[37] S. M. Almufti., et al: Real Time face-mask detection with Arduino to prevent spreading of COVID-19, Qubahan Academic Journal, Vol. 1, No. 2, pp. 39-46, 2021.

[38] A. Kaur and A. Jasuja: Cost Effective Remote Health Monitoring System Based on IoT Using Arduino UNO. Advances in Computer Science and Information Technology (ACSIT)., Vol. 4, No. 2, pp. 80–84, 2017.

[39] R. Turner: Arduino Programming: 2 books in 1 - The Ultimate Beginner’s & Intermediate Guide to Learn Arduino Programming Step by Step. Nelly B. L. International Consulting Ltd, 2018.


Full Text: PDF

DOI: 10.30595/juita.v10i1.11977

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2579-8901