Environment indoor air quality assessment using fuzzy inference system

被引:38
作者
Dionova, Brainvendra Widi [1 ]
Mohammed, M. N. [2 ]
Al-Zubaidi, S. [3 ]
Yusuf, Eddy [4 ]
机构
[1] Management & Sci Univ, Sch Grad Studies, Shah Alam 40100, Selangor, Malaysia
[2] Management & Sci Univ, Fac Informat Sci & Engn, Dept Engn & Technol, Shah Alam 40100, Selangor, Malaysia
[3] Univ Baghdad, Al Khwarizmi Coll Engn, Dept Automated Mfg Engn, Baghdad 10071, Iraq
[4] Inst Teknol & Kesehatan Jakarta, Fac Pharm, Java 17411, Indonesia
关键词
Fuzzy inference system (FIS); Clustering technique; Environment indoor air quality index (EIAQI); Environment indoor air quality (EIAQ); Indoor air; quality index (IAQI); Thermal comfort index (TCI); HUMAN HEALTH; THERMAL COMFORT; TEMPERATURE; POLLUTION; IMPACT;
D O I
10.1016/j.icte.2020.05.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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. (C) 2020 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.
引用
收藏
页码:185 / 194
页数:10
相关论文
共 66 条
[1]  
Aggarwal A, 2017, 2017 INTERNATIONAL CONFERENCE ON INFOCOM TECHNOLOGIES AND UNMANNED SYSTEMS (TRENDS AND FUTURE DIRECTIONS) (ICTUS), P786, DOI 10.1109/ICTUS.2017.8286113
[2]  
Al-Youif S, 2018, 2018 IEEE SYMPOSIUM ON COMPUTER APPLICATIONS & INDUSTRIAL ELECTRONICS (ISCAIE 2018), P230, DOI 10.1109/ISCAIE.2018.8405475
[3]  
Ali MAM, 2018, 2018 IEEE CONFERENCE ON SYSTEMS, PROCESS AND CONTROL (ICSPC), P44, DOI 10.1109/SPC.2018.8704143
[4]  
Almahdi AA, 2018, J ENERGY, V2018, P1
[5]  
Alves C.A., 2019, ATMOS POLLUT RES
[6]   Air quality assessment using a weighted Fuzzy Inference System [J].
Angel Olvera-Garcia, Miguel ;
Carbajal-Hernandez, Jose J. ;
Sanchez-Fernandez, Luis P. ;
Hernandez-Bautista, Ignacio .
ECOLOGICAL INFORMATICS, 2016, 33 :57-74
[7]  
Anwar F., 2016, CAUSES OF OZONE LAYE, P129
[8]  
Aslam Z, 2017, 2017 INTERNATIONAL CONFERENCE ON ENERGY CONSERVATION AND EFFICIENCY (ICECE), P85, DOI 10.1109/ECE.2017.8248834
[9]   Indoor air quality in a metropolitan area metro using fuzzy logic assessment system [J].
Assimakopoulos, M. N. ;
Dounis, A. ;
Spanou, A. ;
Santamouris, M. .
SCIENCE OF THE TOTAL ENVIRONMENT, 2013, 449 :461-469
[10]  
Asthana P, 2018, 2018 INTERNATIONAL CONFERENCE ON COMPUTATIONAL AND CHARACTERIZATION TECHNIQUES IN ENGINEERING & SCIENCES (CCTES), P36, DOI 10.1109/CCTES.2018.8674076