Novel Framework for Analyzing Air Quality using MatLab
G. Radhika1, A. Padmapriya2

1M. Radhika, M. Phil Scholar, Department of Computer Science, Alagappa University, Karaikudi, India.
2Dr. A. Padmapriya, Associate Professor, Department of Computer Science, Alagappa University, Karaikudi, India. 

Manuscript received on 17 August 2019. | Revised Manuscript received on 21 August 2019. | Manuscript published on 30 September 2019. | PP: 6579-6583 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5463098319/2019©BEIESP | DOI: 10.35940/ijrte.C5463.098319
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Abstract: Nature of the air in city and urban regions is the most significant factor that legitimately impacts the frequency of infections and diminishes the personal satisfaction. Taking suitable choices in an opportune period relies upon the estimation and examination of the parameters of the ongoing air quality checking. On the other hand air contamination is ecological and a social issue. Air contamination is one of the biggest natural wellbeing dangers in the world today. The utilization of multi-parameter air quality observing frameworks makes it conceivable to do an itemized level investigation of real poisons and their sources. These air quality observing frameworks are significant segments in many shrewd city ventures for checking air quality and for controlling the primary poison fixations in urban zones. In this research work a methodology for practical estimation of air quality is proposed. This application has been tried in the city and the estimation was contrasted and the yield information of the neighborhood ecological control expert stations. The results of the performance analysis demonstrate that this methodology can be utilized as an affordable option in contrast to the expert evaluation frameworks. In this research work an investigation on the contamination by traffic framework utilizing dataset with grouping strategy through MatLab.
Keywords: Air quality, Clustering, K-Means, ANN, KNN, Accuracy, Floyd Warshall.

Scope of the Article:
Patterns and Frameworks