City:

 Delhi, India

Organization:

 Bhagwan Parshuram Institute of Technology, Delhi, India

Project Start Date:

 Unknown

Project End Date:

 14 August 2016

Reference:

Shweta Taneja, Dr. Nidhi Sharma, Kettun Oberoi, Yash Navoria (2016).

Predicting trends in air pollution in Delhi using data mining.

1st India International Conference on Information Processing (IICIP). https://ieeexplore.ieee.org/document/7975379

Problem:

The rise in the air pollution rate has affected people with serious health problems like asthma, pneumonia, lung infection etc. Data mining was used to analyze the existing trends in air pollution in Delhi, India and make prediction about the future.

Technical Solution:

·     Time Series Analysis

·     Multilayer Perceptron

·     Linear Regression

Datasets Used:

·     Dataset 1: Air Pollutants data from Central Pollution Control Board (CPCB), From year 2011 to 2015, Month wise

Outcome:

·     Pollutants like NO2 and O3 are likely to increase in future

·     SO2 and CO levels will follow a similar trend of the past

·     PM10 is likely to increase drastically in future due to road and pavement dust and construction work in metro cities.

Issues that arose:

There were no issues with the data sets which were used.

However, the algorithms might change if the number of pollutants is increased.

Status:

  Terminated

Entered by:

  Yash Chahande, yash.chahande@mail.utoronto.ca