Blueprint for a natural language processing powered nexus for regulatory and legal landscape in construction

dc.contributor.authorSaparamadu, PVIN
dc.contributor.authorJayasena, HS
dc.contributor.authorEranga, BAI
dc.contributor.editorSandanayake, YG
dc.contributor.editorWaidyasekara, KGAS
dc.contributor.editorRanadewa, KATO
dc.contributor.editorChandanie, H
dc.date.accessioned2024-09-02T04:29:09Z
dc.date.available2024-09-02T04:29:09Z
dc.date.issued2024
dc.description.abstractThe recent exponential advancements in Natural Language Processing (NLP) are catalysing a paradigm shift in the world, directing the construction industry towards an era of smart construction. The proficiency of NLP in comprehending and assimilating vast quantities of human language data aligns aptly with the construction sector’s exigency for enhanced management of its unstructured textual data. Given the frequent alterations in regulatory frameworks and the dispersed nature of project data, there arises a compelling need for a Natural Language Processing Powered Compliance Management Nexus (NLP-PCMN), which facilitates expedited access to consolidated information via mobile platforms. This study aims to develop a blueprint for implementing an NLP-PCMN in the construction industry. By conducting semi-structured interviews with 20 experts spanning the domains of construction and Artificial Intelligence (AI) alongside a focus group to outline the technological framework of the NLP-PCMN, the research underscores the need to implement such a system. The envisaged system is poised to address challenges such as navigating contract clauses, correspondence analysis and ensuring legal compliance with planning and building codes and legal provisions. The proposed NLP-PCMN presents a comprehensive solution integrating these features through large language models that work as a question-and-answering system. Key findings include the necessity of automating the regulatory and legal data in construction, stakeholder empowerment through NLP-PCMN, identifying the nodes of the NLP-PCMN and the technical blueprint to implement the NLP-PCMN.en_US
dc.identifier.conferenceWorld Construction Symposium - 2024en_US
dc.identifier.departmentDepartment of Building Economicsen_US
dc.identifier.doihttps://doi.org/10.31705/WCS.2024.24en_US
dc.identifier.emailishini@concolabs.comen_US
dc.identifier.emailsuranga@uom.lken_US
dc.identifier.emailisurue@uom.lken_US
dc.identifier.facultyArchitectureen_US
dc.identifier.pgnospp. 306-317en_US
dc.identifier.placeColomboen_US
dc.identifier.proceeding12th World Construction Symposium - 2024en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/22775
dc.identifier.year2024en_US
dc.language.isoenen_US
dc.publisherDepartment of Building Economicsen_US
dc.subjectArtificial Intelligence (AI)en_US
dc.subjectConstruction Lawen_US
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectSmart Constructionen_US
dc.titleBlueprint for a natural language processing powered nexus for regulatory and legal landscape in constructionen_US
dc.typeConference-Full-texten_US

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