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dc.contributor.authorTrani, Marco Lorenzo
dc.contributor.authorMadaschi, Federica
dc.date.accessioned2024-04-02T15:44:33Z
dc.date.available2024-04-02T15:44:33Z
dc.date.issued2023
dc.identifierONIX_20240402_9791221502893_11
dc.identifier.issn2704-5846
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/89042
dc.description.abstractThe rapid progress of artificial intelligence (AI) has prompted the exploration of its potential applications in the construction industry, although at a slower rate. Since the starting point of a design is the analysis of the site’s constraints, the purpose of the ongoing research is the application of artificial intelligence in risk assessment for site areas. The primary objective of this research project is to develop an interactive map that employs AI to identify potential surface and aerial interferences. This map aims to support planners, engineers, and architects during the site context analysis phase by providing real-time visualization of obstacles. The interactive map allows users to explore and analyze identified obstacles, enabling cluster markers and filtering of features. The results obtained from applying this approach in Milan, Italy, demonstrate its functionality and usability, highlighting the tool's ability to provide valuable information in both localized and citywide scenarios. Potential improvements such as size assessment and advanced marker generation are also being examined to enhance the management of surface and air interferences. The goal is to enhance the tool's functionality, accuracy, and planning efficiency in construction projects
dc.languageEnglish
dc.relation.ispartofseriesProceedings e report
dc.subject.classificationthema EDItEUR::U Computing and Information Technology
dc.subject.otherImage Segmentation
dc.subject.otherRisk Assessment
dc.subject.otherConstruction Site
dc.subject.otherClustering Techniques
dc.titleChapter Image Segmentation Applied to Urban Surface and Aerial Constraints Analysis
dc.typechapter
oapen.identifier.doi10.36253/979-12-215-0289-3.90
oapen.relation.isPublishedBybf65d21a-78e5-4ba2-983a-dbfa90962870
oapen.relation.isbn9791221502893
oapen.series.number137
oapen.pages10
oapen.place.publicationFlorence


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