Mining and analysis of air quality data to aid climate change

Lakshmi Babu Saheer; Mohamed Shahawy; Javad Zarrin

doi:10.1007/978-3-030-49190-1_21

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 proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops
Subtitle of host publication	MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings
Editors	Ilias Maglogiannis, Lazaros Iliadis, Elias Pimenidis
Place of Publication	Cham
Publisher	Springer
Pages	232-243
Number of pages	12
ISBN (Electronic)	9783030491901
ISBN (Print)	9783030491895, 9783030491925
DOIs	https://doi.org/10.1007/978-3-030-49190-1_21
Publication status	Published - 30 May 2020
Externally published	Yes
Event	9th Mining Humanistic Data Workshop - Halkidiki, Greece Duration: 6 Jun 2020 → 7 Jun 2020 Conference number: 9th https://conferences.cwa.gr/mhdw2020/

Publication series

Name	IFIP Advances in Information and Communication Technology
Publisher	Springer
Volume	585
ISSN (Print)	1868-4238
ISSN (Electronic)	1868-422X

Workshop

Workshop	9th Mining Humanistic Data Workshop
Abbreviated title	MHDW
Country/Territory	Greece
City	Halkidiki
Period	6/06/20 → 7/06/20
Other	The 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	https://conferences.cwa.gr/mhdw2020/

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-49190-1_21

Cite this

Babu Saheer, L., Shahawy, M., & Zarrin, J. (2020). Mining and analysis of air quality data to aid climate change. In I. Maglogiannis, L. Iliadis, & E. Pimenidis (Eds.), Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops: MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings (pp. 232-243). (IFIP Advances in Information and Communication Technology; Vol. 585). Springer. https://doi.org/10.1007/978-3-030-49190-1_21

Babu Saheer, Lakshmi ; Shahawy, Mohamed ; Zarrin, Javad. / Mining and analysis of air quality data to aid climate change. Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops: MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings. editor / Ilias Maglogiannis ; Lazaros Iliadis ; Elias Pimenidis. Cham : Springer, 2020. pp. 232-243 (IFIP Advances in Information and Communication Technology).

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title = "Mining and analysis of air quality data to aid climate change",

abstract = "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.",

author = "{Babu Saheer}, Lakshmi and Mohamed Shahawy and Javad Zarrin",

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year = "2020",

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editor = "Ilias Maglogiannis and Lazaros Iliadis and Elias Pimenidis",

booktitle = "Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops",

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Babu Saheer, L, Shahawy, M & Zarrin, J 2020, Mining and analysis of air quality data to aid climate change. in I Maglogiannis, L Iliadis & E Pimenidis (eds), Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops: MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings. IFIP Advances in Information and Communication Technology, vol. 585, Springer, Cham, pp. 232-243, 9th Mining Humanistic Data Workshop, Halkidiki, Greece, 6/06/20. https://doi.org/10.1007/978-3-030-49190-1_21

Mining and analysis of air quality data to aid climate change. / Babu Saheer, Lakshmi; Shahawy, Mohamed; Zarrin, Javad.

Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops: MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings. ed. / Ilias Maglogiannis; Lazaros Iliadis; Elias Pimenidis. Cham : Springer, 2020. p. 232-243 (IFIP Advances in Information and Communication Technology; Vol. 585).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Babu Saheer, Lakshmi

AU - Shahawy, Mohamed

AU - Zarrin, Javad

N1 - Conference code: 9th

PY - 2020/5/30

Y1 - 2020/5/30

N2 - 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.

AB - 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.

U2 - 10.1007/978-3-030-49190-1_21

DO - 10.1007/978-3-030-49190-1_21

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SN - 9783030491895

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BT - Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops

A2 - Maglogiannis, Ilias

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PB - Springer

CY - Cham

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Y2 - 6 June 2020 through 7 June 2020

ER -

Babu Saheer L, Shahawy M, Zarrin J. Mining and analysis of air quality data to aid climate change. In Maglogiannis I, Iliadis L, Pimenidis E, editors, Artificial Intelligence Applications and Innovations, AIAI 2020 IFIP WG 12.5 International Workshops: MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020 : proceedings. Cham: Springer. 2020. p. 232-243. (IFIP Advances in Information and Communication Technology). https://doi.org/10.1007/978-3-030-49190-1_21

Mining and analysis of air quality data to aid climate change

Abstract

Publication series

Workshop

Keywords

UN SDGs

Access to Document

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Cite this