Main Article Content
Abstract
Air Pollution is the world’s largest single environmental health risk, which is mostly due to the pollutants of Particulate matter of aerodynamic size from 2.5 micrometres to 10 micrometres, which are emitted mostly by burning coals, plants, heavy metals and other petrochemical products. Quality of the air in city and urban areas is the most important factor that directly influences the incidence of diseases and decreases the quality of life. Taking appropriate decisions in a timely period depends on the measurement and analysis of the parameters of the air, which creates the need for the development of real time air quality monitoring. The use of air quality monitoring systems makes it possible to do a detailed level analysis of major pollutants and their sources. These monitoring systems are important components in many smart city projects for monitoring air quality and for controlling the main pollutant concentrations in urban areas. In this paper we present an approach for cost-effective measurement of relevant environmental parameters, based on a scalable sensor array. The measure air quality is updated to cloud and data is processed to find the level difference in each area depending on number of trees in that area, because trees absorb harmful gases such as sulphur dioxide, carbon monoxide, carbon dioxide along with PM particles of various sizes.