Fuzzy Inference of Air Quality – A case study of Vadodara City
2023
Seema, Nihalani
Abstract: Air Quality Index (AQI) is derived from a series of observations of different air pollutants for reporting air quality. The severity of air pollution and its impacts on the general public are typically reported using the air quality index. Different methods have been developed by various regulatory agencies and scientists, to calculate the AQI using aggregation methods involving critical pollutants. This paper presents a comparison between conventional AQI and Fuzzy AQI. 20 sampling locations were chosen for Vadodara city in order to investigate the effects of urban air pollution, and ambient air quality was measured twice a week from October 2017 to February 2018. The Central Pollution Control Board (CPCB) method formulas were used to calculate the traditional Air Quality Index using the measured values of Coarse particulate matter (PM10), Sulphur dioxide (SO2), and Oxides of nitrogen (NOX). Additionally, the membership functions were provided as input to the Mamdani fuzzy inference system (FIS) for the fuzzy logic system, and the fuzzy air quality index (FAQI) was calculated. The computed conventional AQI values were compared with FAQI values. A close co-relation was observed between conventional AQI and fuzzy AQI values. The application of the fuzzy inference system demonstrates its capability to manage difficult issues including data ambiguity. The findings clearly show that the FIS is capable of resolving inherent discrepancies and interpreting complex conditions.
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