Air Quality Prediction using Artificial Intelligence
P. ShreeNandhini1, P. Amudha2, S. Sivakumari3
1P.ShreeNandhin*i, Research scholar, Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India.
2Dr.P.Amudha,Associate Professor Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India.
3Dr.S.Sivakumari, Professor and Head, Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 10, 2020. | PP: 1417-1420 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2795039520/2020©BEIESP | DOI: 10.35940/ijitee.E2795.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Due to the critical impacts of air pollution, prediction and monitoring of air quality in urban areas are essential tasks. However, because of the dynamic nature and high Spatio-temporal variability, the prediction of the air pollutant concentrations is a complex Spatio-temporal problem. The data is collected in specific area such as climate condition and vehicular pollutant occurring in the peak hours. the predication process is used to compare the algorithm artificial neural network and support vector machine process. This paper presents a survey on Air quality prediction using artificial intelligence
Keywords: Spatio-Temporal, Ambient Air Pollution, Support Vector Machine,
Scope of the Article: Ventilation and Indoor Air Quality