dc.contributor.author |
Saparamadu, PVIN |
|
dc.contributor.author |
Jayasena, HS |
|
dc.contributor.author |
Eranga, BAI |
|
dc.contributor.editor |
Sandanayake, YG |
|
dc.contributor.editor |
Waidyasekara, KGAS |
|
dc.contributor.editor |
Ranadewa, KATO |
|
dc.contributor.editor |
Chandanie, H |
|
dc.date.accessioned |
2024-09-02T04:29:09Z |
|
dc.date.available |
2024-09-02T04:29:09Z |
|
dc.date.issued |
2024 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/22775 |
|
dc.description.abstract |
The 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.language.iso |
en |
en_US |
dc.publisher |
Department of Building Economics |
en_US |
dc.subject |
Artificial Intelligence (AI) |
en_US |
dc.subject |
Construction Law |
en_US |
dc.subject |
Natural Language Processing (NLP) |
en_US |
dc.subject |
Smart Construction |
en_US |
dc.title |
Blueprint for a natural language processing powered nexus for regulatory and legal landscape in construction |
en_US |
dc.type |
Conference-Full-text |
en_US |
dc.identifier.faculty |
Architecture |
en_US |
dc.identifier.department |
Department of Building Economics |
en_US |
dc.identifier.year |
2024 |
en_US |
dc.identifier.conference |
World Construction Symposium - 2024 |
en_US |
dc.identifier.place |
Colombo |
en_US |
dc.identifier.pgnos |
pp. 306-317 |
en_US |
dc.identifier.proceeding |
12th World Construction Symposium - 2024 |
en_US |
dc.identifier.email |
ishini@concolabs.com |
en_US |
dc.identifier.email |
suranga@uom.lk |
en_US |
dc.identifier.email |
isurue@uom.lk |
en_US |
dc.identifier.doi |
https://doi.org/10.31705/WCS.2024.24 |
en_US |