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Multimodal Data Fusion and Deep Learning for Predicting Air Pollution at Construction Sites

dc.contributor.authorZhang, Ruichuan
dc.contributor.authorSapkota, Jharana
dc.contributor.authorKrall, Jenna
dc.date.accessioned2026-08-20T21:26:46Z
dc.date.available2026-08-20T21:26:46Z
dc.date.copyright2025/11/17
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-7003.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314465
dc.description.abstractAbstractThe construction sector is a major contributor to air pollution, emitting large volumes of particulate matter that pose significant health and environmental risks. Construction activities, such as excavation, material transport, and vehicle ...
dc.publisherAmerican Society of Civil Engineers
dc.titleMultimodal Data Fusion and Deep Learning for Predicting Air Pollution at Construction Sites
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue2
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-7003
dc.journal.fristpage04025132-1
dc.journal.lastpage04025132-14
dc.page14
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 002
dc.contenttypeFulltext


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