Environment indoor air quality assessment using fuzzy inference system

• Published in: ICT express Vol. 6; no. 3; pp. 185 - 194
• Main Authors: Dionova, Brainvendra Widi, Mohammed, M.N., Al-Zubaidi, S., Yusuf, Eddy
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2020; Elsevier; 한국통신학회
• Subjects: Clustering technique; Environment indoor air quality (EIAQ); Environment indoor air quality index (EIAQI); Fuzzy inference system (FIS); Indoor air quality index (IAQI); Thermal comfort index (TCI); 전자/정보통신공학; Indoor air quality index (IAQI); Environment indoor air quality index (EIAQI); Clustering technique; Fuzzy inference system (FIS); Thermal comfort index (TCI); Environment indoor air quality (EIAQ)
• ISSN: 2405-9595; 2405-9595
• DOI: 10.1016/j.icte.2020.05.007

Environment indoor quality (EIQ) is a significant aspect of the built environment to maintain occupant health, comfort, prosperity and productivity. One of the most critical issues on EIQ is the environment of indoor air quality (EIAQ). Indoor air pollution has a big impact on the degradation quality of human life due to harmful chemicals and other toxic materials that it is worsened by ten times than the outdoor air pollution. Environment indoor air quality index (EIAQI) does a crucial role in determining the EIAQ that is good for a healthy human life by combining indoor air quality index (IAQI) and thermal comfort index (TCI). This research presents an EIAQ monitoring and controlling system based on fuzzy logic controller (FLC) to identify, classify and calculate the EIAQI value expressed in four categories: excellent, good, bad and worst. Additionally, the clustering technique is used to categorize the air pollutants according to the similarities characteristics and human health impact. EIAQI values are used as index references to set the control system automatically. The control system is used as a system that can notify the status level and reduce indoor air and thermal comfort pollutants and is in the form of fans, inlet–outlet exhaust, and buzzer and LED. Therefore, these models are an appropriate tool for identifying, classifying, assessing, providing guidance to increase the quality of human life.