Manuscript Number : CSEIT172657
An Assessment on Effects of Air Pollution Using Machine Learning
Authors(2) :-S. Jeya, Dr. L. Sankari
Atmospheric pollutants P.M10, SO2, NO2, CO, and Ground level Ozone affect our ecosystems and are harmful to human health. Air Pollution has been identified to cause several respiratory and heart ailments which lead to thousands of deaths every year. Children are more susceptible to such ailments than adults. Metropolitan areas are worst affected from air pollution caused by industries and automobiles. With the help of statistical models built using machine learning and data mining techniques, computerised medical support systems could be designed to aid in treating diseases triggered by pollution. Also the models can be useful in predicting future pollution trends based on current data in order to help manage and control toxic atmospheric emissions.
Research Scholar, Department of Computer Science, Sri Ramakrishna College of Arts and Science for Women, Coimbatore, India
Dr. L. Sankari
Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts and Science for Women, Coimbatore, India
Air Pollution, Respiratory ailments, Machine learning, Air Quality.
- Ozgur Kisi1, Kulwinder Singh Parmar2, Kirti Soni3, Vahdettin Demir4, "Modelling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models”, Air Quality, Atmosphere & Health, vol.10, issue 7, pp.873-883, 2017.
- M. Deepa1 & M. Rajalakshmi2 & R. Nedunchezhian2, "Impact of Air Pollution on Respiratory Diseases: Correlation and Classification by Multivariate Data Analysis”, Data-Enabled Discovery and Applications (2017) 1:3. https://doi.org/10.1007/s41688-017-0004-z.
- Umesh M. Lanjewar1, J. J. Shah2 , "Air Pollution Monitoring & Tracking System Using Mobile Sensors and Analysis of Data Using Data Mining”, International Journal of Advanced Computer Research, Vol.2 No.4 Issue-6 Dec.2012.
- Gunita Yadav, Dr. Nitin Mishra, "Air Pollution Trend Analysis Using Sen Estimator Method”, IJARCSSE, Vol. 5, Issue 7, pp.1073-1080, July 2015.
- R. K. Xie & H. M. Seip & L. Liu & D. S. Zhang, "Characterization of individual airborne particles in Taiyuan City, China”, Air Qual Atmos Health (2009) 2(3):123–131 DOI 10.1007/s11869-009-0039-x
- H.-H. Kim & C.-S. Lee & J.-M. Jeon & S.-D. Yu & C.-W. Lee & J.-H. Park & D.-C. Shin & Y.-W. Lim, "Analysis of the association between air pollution and allergic diseases exposure from nearby sources of ambient air pollution within elementary school zones in four Korean cities”, Environmental Science and Pollution Research, July 2013 vol.20, issue 7, pp 4831–4846 DOI 10.1007/s11356-012-1358-2
- Chao-Hui Leea, Jessie Chia-Yu Chena, Vincent S. Tsenga,b , "A novel data mining mechanism considering bio-signal and environmental data with applications on asthma monitoring”, Computer methods and programs in biomedicine. Jan 2011, 101(1):44-61. doi: 10.1016/ j.cmpb. 2010.04.016.
- Swati Vitkar, "Comparative Analysis of Various Data Mining Prediction Algorithms, Demonstrated using Air Pollution Data of Navi Mumbai”, Research Journal of Chemical and Environmental Sciences, Vol 5 , pp. 79-85, February 2017.
- Machine learning: the power and promise of computers that learn by example Issued: April 2017 DES 4702 ISBN: 978-1-78252-259-1.
- Festim Halili1, Avni Rustemi2, "Predictive Modelling: Data Mining Regression Technique Applied in a Prototype”, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.8, August- 2016, pg. 207-215.
- Priyanka Gaur, "Neural Networks in Data Mining”, International Journal of Electronics and Computer Science Engineering (IJECSE), Vol.1, No.3, pp. 1449-1453.
- Guang-Bin Huang, Dian Hui Wang, Yuan Lan, "Extreme learning machines: a survey”, International Journal of Machine Learning & Cybernetics, June 2011, vol. 2, issue 2, pp 107–122.
- Subhash Chandra Pandey, "Data Mining Techniques for Medical Data: A Review”, International conference on Signal Processing, Communication, Power and Embedded System, 2016 IEEE, pp.972-982, DOI: 10.1109/ SCOPES. 2016. 7955586.
- Juliet Rani Rajan1, Chilambu Chelvan A2, "Prognostic system for early diagnosis of paediatric lung disease using artificial intelligence”, Current Pediatric Research 2017 Vol. 21 Issue 1, pp.31-34.
- Shomona Gracia Jacob. R Geetha Ramani, "Data Mining in Clinical Data Sets: A Review”, International Journal of Applied Information Systems (IJAIS), Vol. 4, No.6, pp. 15-26, December 2012.
Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 197-202
Manuscript Number : CSEIT172657
Publisher : Technoscience Academy
URL : http://ijsrcseit.com/CSEIT172657