An analysis of air pollution control and equipment selection using a fuzzy approach

Air pollution is one of the most important causes of acute and chronic respiratory diseases. Every year, a large number of children and the elderly seek respiratory diseases, all of which are caused by air pollution; They lose their lives. Air quality generally affects life and the environment. Low air quality has claimed many lives and polluted the environment around the world, and is much more severe in some countries where air quality monitoring systems are scarce or non-existent. Dirty air is caused by the growth of industrialization, urbanization, flights and road traffic. Air pollution is still a silent killer, and if left unchecked, can still lead to health problems such as heart disease, stroke, and chronic respiratory illness that can lead to death. In this paper, Kampala air quality index forecasting model was designed based on fuzzy logic inference system to determine the air quality of Kampala city according to the concentration of air pollutants (nitrogen dioxide, sulfur dioxide and fine particles ۲.۵). It can be seen that fuzzy logic algorithms are able to determine the air quality index and therefore it can be used to predict and estimate the air quality index in real time, based on air pollutant concentrations. Hence, it can reduce the effects of air pollution on both humans and the environment.

Keywords:

Air pollution , fuzzy logic , Kampala , Air Quality Index.