Fuzzy logic-based improved ventilation system for the pharmaceutical industry

  • Authors

    • Sam Matiur Rahman Department of Software Engineering, Daffodil International University, Dhaka, Bangladesh
    • Mohammad Fazle Rabbi
    • Omar Altwijri
    • Mahdi Alqahtani
    • Tasriva Sikandar
    • Izzeldin Ibrahim Abdelaziz
    • Md. Asraf Ali
    • Kenneth Sundaraj
    2018-04-29
    https://doi.org/10.14419/ijet.v7i2.9985
  • Fuzzy Inference System, Air-Conditioning, Pharmaceutical Laboratories, Smart Ventilation.

  • Abstract

    Indoor air quality in pharmaceutical industry plays a vital role in the production and storing of medicine. Stable indoor environment including favorable temperature, humidity, air flow and number of microorganisms requires consistent monitoring. This paper aimed to develop a fuzzy logic-based intelligent ventilation system to control the indoor air quality in pharmaceutical sites. Specifically, in the proposed fuzzy inference system, the ventilation system can control the air flow and quality in accordance with the indoor temperature, humidity, air flow and microorganisms in the air. The MATLAB® fuzzy logic toolbox was used to simulate the performance of the fuzzy inference system. The results show that the efficiency of the system can be improved by manipulating the input-output parameters according to the user’s demands. Compared with conventional heating, ventilation and air-conditioning (HVAC) systems, the proposed ventilation system has the additional feature of the existence of microorganisms, which is a crucial criterion of indoor air quality in pharmaceutical laboratories.

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  • How to Cite

    Rahman, S. M., Rabbi, M. F., Altwijri, O., Alqahtani, M., Sikandar, T., Abdelaziz, I. I., Ali, M. A., & Sundaraj, K. (2018). Fuzzy logic-based improved ventilation system for the pharmaceutical industry. International Journal of Engineering & Technology, 7(2), 640-645. https://doi.org/10.14419/ijet.v7i2.9985

    Received date: 2018-03-08

    Accepted date: 2018-04-04

    Published date: 2018-04-29