Spatial air quality prediction in urban areas via message passing
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- dc.contributor.author Calo Oliveira, Sergio
- dc.contributor.author Bistaffa, Filippo
- dc.contributor.author Jonsson, Anders
- dc.contributor.author Gómez, Vicenç
- dc.contributor.author Viana, Mar
- dc.date.accessioned 2025-05-29T08:59:25Z
- dc.date.available 2025-05-29T08:59:25Z
- dc.date.issued 2024
- dc.description.abstract Air pollution in urban areas poses a significant and pressing challenge for modern society. Unfortunately, the existing network of pollution detectors in many cities is limited in scope and fails to adequately cover the entire geographical area. Consequently, the implementation of spatial prediction algorithms becomes essential to generate high-resolution data. In this paper, we introduce two significant contributions: 1) We formalize the air pollution prediction problem as a Maximum A Posteriori (MAP) estimate within the framework of a Markov Random Field and 2) we propose a message-passing algorithm, which stands out as an efficient solution that surpasses the current state of the art. The experimental procedure has been carried out using the case study of the city of Barcelona, based on a dataset extracted from the BCN Open Data portal.
- dc.format.mimetype application/pdf
- dc.identifier.citation Calo S, Bistaffa F, Jonsson A, Gómez V, Viana M. Spatial air quality prediction in urban areas via message passing. Eng Appl Artif Intell. 2024 July;133(Pt B):108191. DOI: 10.1016/j.engappai.2024.108191
- dc.identifier.doi http://dx.doi.org/10.1016/j.engappai.2024.108191
- dc.identifier.issn 0952-1976
- dc.identifier.uri http://hdl.handle.net/10230/70555
- dc.language.iso eng
- dc.publisher Elsevier
- dc.relation.ispartof Engineering Applications of Artificial Intelligence. 2024 July;133(Pt B):108191
- dc.rights © 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
- dc.subject.keyword Air quality
- dc.subject.keyword Graph neural networks
- dc.subject.keyword Graph signal reconstruction
- dc.title Spatial air quality prediction in urban areas via message passing
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion