Mining and analysis of air quality data to aid climate change

Lakshmi Babu Saheer*, Mohamed Shahawy, Javad Zarrin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


The data science and AI community has gathered around the world to support tackling the climate change problem in different domains. This research aims to work on the air quality through emissions and pollutant concentration data along with vegetation information. Authorities especially in urban cities like London have been very vigilant in monitoring these different aspects of air quality and reliable sources of big data are available in this domain. This study aims to mine and collate this information spread all over the place in different formats into usable knowledge base on which further data analysis and powerful Machine Learning approaches can be built to extract strong evidences useful in building better policies around climate change.

Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops
Subtitle of host publicationMHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings
EditorsIlias Maglogiannis, Lazaros Iliadis, Elias Pimenidis
Place of PublicationCham
Number of pages12
ISBN (Electronic)9783030491901
ISBN (Print)9783030491895, 9783030491925
Publication statusPublished - 30 May 2020
Externally publishedYes
Event9th Mining Humanistic Data Workshop - Halkidiki, Greece
Duration: 6 Jun 20207 Jun 2020
Conference number: 9th

Publication series

NameIFIP Advances in Information and Communication Technology
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X


Workshop9th Mining Humanistic Data Workshop
Abbreviated titleMHDW
OtherThe Mining Humanistic Data Workshop (MHDW) aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing artificial intelligence, data matching, fusion and mining and knowledge discovery and management techniques to data derived from all areas of Humanistic Sciences.
Internet address


  • Data mining and analysis
  • Data pre-processing
  • Air quality
  • Climate change
  • Urban planning and machine learning
  • Geographic information systems


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