This paper is published in Volume-4, Issue-2, 2018
Area
Machine Learning
Author
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H
Org/Univ
Kammavari Sangha Institute of Technology, Bengaluru, Karnataka, India
Keywords
Collaborative Filtering, Data Mining, Machine learning, Web-based application.
Citations
IEEE
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H. Prediction of urban air pollution by a machine learning method, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H (2018). Prediction of urban air pollution by a machine learning method. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.
MLA
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H. "Prediction of urban air pollution by a machine learning method." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H. Prediction of urban air pollution by a machine learning method, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H (2018). Prediction of urban air pollution by a machine learning method. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.
MLA
Saniya Afshan, Nithin S, Venkata Sai Nishanth, S Nithin, Aditya Pai H. "Prediction of urban air pollution by a machine learning method." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.
Abstract
In addition to the impact of rapid population growth and urbanization, the level of pollution in the cities is largely modulated by meteorological factors. A compilation of meteorological data in many cities is available in Indian Government websites. They give the concentration levels of several parameters including PM2.5, NO2, CO, etc. With the help of this website data, we use Data Mining Prediction technique Collaborative Filtering and Machine learning to predict the next day data and compare with actual data. This elementary research intends to be an introductory step in the development of a web-based platform for the awareness of the residents of urban areas about the risk to human health, with potential future application in other urban areas. To make the real-time scenario Service Orientated Web Architecture is used in this system.