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Design and Development of IoT Based Medical Cleanroom

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Advances in Computational Collective Intelligence (ICCCI 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1864))

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Abstract

In this study, we have developed and analyzed the implementation of an IoT system for a clean room, which encompasses an automated monitoring system utilizing IoT sensors. The performance of the proposed system was evaluated through experiments conducted at the Faculty of Information Technology, KazNU (Kazakhstan). Manual tests were performed to verify the accuracy of the sensor data, resulting in a data accuracy rate of approximately 99%. The findings indicate the reliability of the system, making it suitable for effectively connecting urban and suburban park communities. The article focuses on addressing the issue of regulating heat supply and air conditioning within enclosed spaces. We describe an automated system designed to monitor the dynamic characteristics of these sensors, comprising a software and hardware complex for configuring a test bench and analyzing sensor parameters related to dynamic temperature control and air conditioning. The primary objective of this system is to automate the control of air conditioning and maintain a desired temperature within a single room.

The system performs several functions, including control of the Google Coral USB Accelerator, configuration of the ADC, and determination of the amplitude-frequency and phase-frequency characteristics of temperature sensors, switches, leak sensors, and air conditioning units. These determinations are based on experimental studies conducted on a sensor dynamics monitoring stand and monitored using the SCADA Genesis64 program. The article presents the test bench schematic, the general algorithm of system operation, and screenshots of the program interface. The software for the automated temperature control and air conditioning system is developed using ModBus TCP, OPC UA, and SCADA programs as the foundation.

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References

  1. Zheng, K., Zhao, S., Yang, Z., Xiong, X., Xiang, W.: Design and implementation of LPWA-based air quality monitoring system. IEEE Access 4, 3238–3245 (2016). https://doi.org/10.1109/ACCESS.2016.2582153

    Article  Google Scholar 

  2. Tong, S., Wang, T., Li, Y., Chen, B.: A combined backstepping and stochastic small-gain approach to robust adaptive fuzzy output feedback control. In: IEEE Trans. Fuzzy Syst. 21(2), 314–327 (2013)

    Google Scholar 

  3. Daisey, J.M., Angell, W.J., Apte, M.G.: Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information. Indoor Air 13(1), 53–64 (2003)

    Article  Google Scholar 

  4. Postolache, O.A., Dias Pereira, J.M., Silva Girao, P.M.B.: Smart sensors network for air quality monitoring applications. IEEE Trans. Instrum. Meas. 58(9), 3253–3262 (2009)

    Google Scholar 

  5. Tran, T.V., Dang, N.T., Chung, W.Y.: Battery-free smart-sensor system for real-time indoor air quality monitoring. Sens. Actuators B Chem. 248, 930–939 (2017)

    Article  Google Scholar 

  6. On approval of sanitary rules “Sanitary and epidemiological requirements for objects in the field of circulation of medicines, medical devices and medical equipment”. http://law.gov.kz/client/#!/doc/54528/rus/13.08.2010. Last accessed 22 Dec 2022

  7. Ha, Q.P., Metia, S., Phung, M.D.: Sensing data fusion for enhanced indoor air quality monitoring. IEEE Sens. J. 20(8), 4430–4441 (2020)

    Google Scholar 

  8. Pope, D.D., Ezzati, M.: Fine-particulate air pollution and life expectancy in the United States. New Eng. J. Med. 360(4), 376–386 (2009)

    Google Scholar 

  9. Brienza, S., Galli, A., Anastasi, G., Bruschi, P.: A low-cost sensing system for cooperative air quality monitoring in urban areas. Sensors 15, 12242–12259 (2015)

    Google Scholar 

  10. Hung, F.H.: An adaptive indoor air quality control scheme for minimizing volatile organic compounds density. IEEE Access 8, 22357–22365 (2020)

    Google Scholar 

  11. Zheng, H., Xiong, K., Fan, P., Zhong, Z.: Data Analysis on Outdoor–Indoor Air Quality Variation: Buildings’ Producing Dynamic Filter Effects. In: IEEE Systems Journal, vol. 13, no. 4, pp. 4386–4397, (2019)

    Google Scholar 

  12. Saad, S.M., Andrew, A.M., Shakaff, A.Y.M., Saad, A.R.M., Kamarudin, A.M.Y., Zakaria, A.: Classifying sources influencing indoor air quality (IAQ) using artificial neural network (ANN). Sensors 15, 11665–11684 (2015)

    Google Scholar 

  13. Elbayoumi, M., Ramli, N.A., Md Yusof, N.F.F., Al Madhoun W.: Spatial and seasonal variation of particulate matter (PM10 and PM2.5) in Middle Eastern classrooms. Atmos. Environ. 80, 389–397 (2013)

    Google Scholar 

  14. Wei, W., Ramalho, O., Malingre, L., Sivanantham, S., Little, J.C., Mandin, C.: Machine learning and statistical models for predicting indoor air quality. Indoor Air 29(5), 704–726 (2019)

    Google Scholar 

  15. Zhao, L., Wu W., Li, S.: Design and implementation of an IoT-based indoor air quality detector with multiple communication interfaces. IEEE Internet of Things J. 6(6), 9621–9632 (2019)

    Google Scholar 

  16. Mitova, M., Tomov, P., Kunicina, N., Patlins, A., Mansurova M., Namsrai, O.E.: Towards to sustainability of education: the mutual cooperation with partners in Smart city project. In: 2022 IEEE 7th International Energy Conference (ENERGYCON), pp. 1–6 (2022)

    Google Scholar 

  17. Tasmurzayev, N., Amangeldy, B., Baigarayeva, Z., Mansurova, M., Resnik, B., Amirkhanova, G.: Improvement of HVAC system using the intelligent control systemю In: 2022 IEEE 7th International Energy Conference (ENERGYCON), pp. 1–6 (2022)

    Google Scholar 

  18. Tasmurzayev, N.M., Amangeldy, B.S., Nurakhov, E.S., Mukhanbet, A.A., Yeltay, Z.: Implementation of an intelligent control system for heat distribution in rooms. In: 2021 IEEE International Conference on Smart Information Systems and Technologies (SIST), Nur-Sultan, Kazakhstan, pp. 1–5 (2021)

    Google Scholar 

  19. Sodiq, A., Moazzam, A.K., Mahmoud, N., Abdulkarem, A.: Addressing COVID-19 contagion through the HVAC systems by reviewing indoor airborne nature of infectious microbes: will an innovative air recirculation concept provide a practical solution? Environ. Res. 199, 111329 (2021)

    Google Scholar 

  20. Junwei, D., Chuck W.Y., Shi-Jie C.: HVAC systems for environmental control to minimize the COVID-19 infection. Indoor Built Environ. 29, 1195–1201 (2020)

    Google Scholar 

  21. Leonov A.V.: Internet of things: security problems. Omsk Scientific Bulletin, Russia (2015)

    Google Scholar 

  22. Varlamov, I.G.: New generation SCADA. Evolution of technologies-revolution of the building system. In: Automated Information and Control Systems in Power Engineering, Russia (2016)

    Google Scholar 

  23. Tasmurzayev, N., Amangeldy, B., Nurakhov, Y., Akhmed-Zaki, D., Baigarayeva, Z.: Intelligent thermal accumulator operation control system based on renewable energy sources. In: Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics – ICINCO, pp. 737–742 (2021)

    Google Scholar 

  24. Nolan, K.E., Guibene, W., Kelly, M.Y.: An evaluation of low power wide area network technologies for the internet of things. In: Proceeding of International Wireless, Germany (2016)

    Google Scholar 

  25. Soumaya, E.B., et al.: IoT-based smart airflow system for retrofitting commercial variable air volume HVAC systems. IFAC-PapersOnLine 55, 444–449 (2022)

    Google Scholar 

  26. Pavlova, Z., Krasnov. A., Baltin, R.R.: Modern technologies for receiving and transmitting measurement information for the organization of sensor networks for monitoring oil and gas industry objects. Int. Res. J. 202–206 (2017)

    Google Scholar 

  27. Bartlett, G., Heidemann, J., Papadopoulos, C.: Understanding passive and active service discovery. In: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, ACM (2007)

    Google Scholar 

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Acknowledgement

This work was funded by Committee of Science of Republic of Kazakhstan AP09260767 “Development of an intellectual information and analytical system for assessing the health status of students in Kazakhstan” (2021–2023).

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Authors and Affiliations

  1. Al-Farabi Kazakh National University, Al-Farabi avenue, 71, Almaty, Kazakhstan

    Bibars Amangeldy, Nurdaulet Tasmurzayev, Madina Mansurova, Baglan Imanbek & Talsyn Sarsembayeva

Authors
  1. Bibars Amangeldy
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  2. Nurdaulet Tasmurzayev
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  3. Madina Mansurova
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  4. Baglan Imanbek
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  5. Talsyn Sarsembayeva
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Corresponding author

Correspondence to Bibars Amangeldy .

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Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Eötvös Loránd University, Budapest, Hungary

    János Botzheim

  3. Eötvös Loránd University, Budapest, Hungary

    László Gulyás

  4. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Nunez

  5. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

  6. University of Münster, Münster, Germany

    Gottfried Vossen

  7. Wrocław University of Science and Technology, Wrocław, Poland

    Adrianna Kozierkiewicz

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Amangeldy, B., Tasmurzayev, N., Mansurova, M., Imanbek, B., Sarsembayeva, T. (2023). Design and Development of IoT Based Medical Cleanroom. In: Nguyen, N.T., et al. Advances in Computational Collective Intelligence. ICCCI 2023. Communications in Computer and Information Science, vol 1864. Springer, Cham. https://doi.org/10.1007/978-3-031-41774-0_36

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  • DOI: https://doi.org/10.1007/978-3-031-41774-0_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41773-3

  • Online ISBN: 978-3-031-41774-0

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