Air quality index (AQI) classification using CO and NO2 pollutants: A fuzzy-based approach

• Main Authors: Teologo, Antipas T., Dadios, Elmer P., Neyra, Romano Q., Javel, Irister M.
• Format: text
• Published: Animo Repository 2019
• Subjects: Air quality; Carbon monoxide; Nitrogen dioxide; Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1533; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2532/type/native/viewcontent
• Institution: De La Salle University

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 (NO2). 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. © 2018 IEEE.