Air Pollution Monitoring & Tracking System Using Mobile Sensors and Analysis of Data Using Data Mining

This study proposes air pollution monitoring system and analysis of pollution data using association rule data mining technique. Association rule data mining technique aims at finding association patterns among various parameters. In this paper, association rule mining is presented for finding association patterns among various air pollutants. For this, Apriori algorithm of association rule data mining is used. Apriori is characterized as a level - by-level complete search algorithm. This algorithm is applied on data captured by various gas sensors for CO, NO2 and SO2 sensors. As association rule mining can produce several sequence rules of contaminants, the proposed system design can enhance the reproducibility, reliability and selectivity of air pollution sensor output.