Analysing environmental impact of large-scale events in public spaces with cross-domain multimodal data fusion

De, Suparna, Wang, Wei, Zhou, Yuchao, Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346, Moessner, Klaus and Alraja, Mansour Naser 2021. Analysing environmental impact of large-scale events in public spaces with cross-domain multimodal data fusion. Computing 103 , pp. 1959-1981. 10.1007/s00607-021-00944-8

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Abstract

In this study, we demonstrate how we can quantify environmental implications of large-scale events and traffic (e.g., human movement) in public spaces, and identify specific regions of a city that are impacted. We develop an innovative data fusion framework that synthesises the state-of-the-art techniques in extracting pollution episodes and detecting events from citizen-contributed, city-specific messages on social media platforms (Twitter). We further design a fusion pipeline for this cross-domain, multimodal data, which assesses the Spatio-temporal impact of the extracted events on pollution levels within a city. Results of the analytics have great potential to benefit citizens and in particular, city authorities, who strive to optimise resources for better urban planning and traffic management.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Publisher:	Springer
ISSN:	0010-485X
Date of Acceptance:	24 March 2021
Last Modified:	10 Nov 2022 10:30
URI:	https://orca.cardiff.ac.uk/id/eprint/147058

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