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Air Quality Index (AQI) Classification using CO and NO2 Pollutants: A Fuzzy-based Approach
- Source :
- TENCON
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- This paper presents a classification algorithm for air quality index (AQI) using fuzzy logic (FL) system. AQI tells the level of cleanliness of the air and provides a corresponding health warning. In this study, two types of input pollutants are only considered which are the carbon monoxide (CO) and nitrogen dioxide (NO 2 ). Each input is classified into six categories that include very low, low, moderate, high, very high and extremely high. Mamdani fuzzy inference system (FIS) is used to process the FL system giving an output of AQI values expressed in six categories: good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy and hazardous. Simulation is performed using MATLAB fuzzy logic toolbox, which provides effective and reliable results.
- Subjects :
- Pollutant
0209 industrial biotechnology
Computer science
Air pollution
02 engineering and technology
medicine.disease_cause
computer.software_genre
Fuzzy logic
020901 industrial engineering & automation
Fuzzy inference system
0202 electrical engineering, electronic engineering, information engineering
medicine
020201 artificial intelligence & image processing
Data mining
Air quality index
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- TENCON 2018 - 2018 IEEE Region 10 Conference
- Accession number :
- edsair.doi...........ca5d2bc03c9a261831797dbfb63855cb