Level: M.Eng.

Potential applications of Natural Language Processing (NLP) in the construction industry

Abstract

The construction industry is undeniably a complex and fragmented sector, facing numerous challenges, including regular cost and schedule overruns in the majority of construction projects, as well as unsatisfactory quality management. In addition, the sector is lagging behind in terms of digitization. More specifically, the Architecture, Engineering and Construction (AEC) sector is one of the least digitized compared to other industries, mainly due to the complexity of projects involving multiple stakeholders resistant to digitization. On the other hand, huge amounts of textual data are generated in a typical construction project. This data is often spread across various formats such as contracts, progress reports and e-mails, making it difficult for all project stakeholders to analyze, archive and retrieve information. Therefore, the implementation of a Natural Language Processing (NLP) solution, a branch of artificial intelligence (AI), offers a way for construction professionals to overcome the challenges posed by this regularly generated massive data. The main aim of this research project is to explore and categorize the potential applications of NLP (Natural Language Processing) in the construction industry for processing and analyzing textual data to obtain construction-related information. Despite the immense potential of NLP, its applications in the construction sector remain relatively unexplored compared to other industries. To achieve these objectives, a well-defined methodology was established, involving semi-structured interviews with construction professionals in various roles related to the design, construction and management of construction projects in Canada, in order to understand their needs, expectations and perceptions regarding the use of NLP in this field. During the interviews, an NLP questionnaire was asked to identify their potential NLP applications, and the benefits and challenges of each NLP sub-domain. Based on the results of the analysis, recommendations will be made for the adoption of these technologies in the construction industry. The recommendations will take into account the needs and expectations of the parties involved in the project, as well as the benefits and challenges of using NLP in this field.

Project results

The results obtained reveal a marked interest among companies in the construction sector in the integration of NLP technology, particularly in the sub-domains of chatbots, information extraction, text classification, response analysis and voice recognition. The study sample for the semi-structured interviews was carefully selected to reflect a balanced distribution between the various key players in the industry, numbering 25 participants, of whom 24% were women and 76% men. Of these, 36% hold positions related to project management in the construction industry, 28% are directors (innovation / BIM / technical), and the remainder are designers, coordinators and BIM professionals. A number of findings emerged regarding the integration of the best application for each stakeholder.
For example, 75% of customer-side professionals place more importance on the information extraction sub-domain to easily access information instead of searching for it in plans and reports. Similarly, 71% of contractors favor chatbots because of their practical benefits on the job site (Reporting / schedules). On the engineering firm side, 62% of professionals assign a high priority to chatbots due to their ability to provide quick answers to common questions and design standards. However, our analysis also highlighted significant challenges, such as data reliability, confidentiality, resistance to change and ease of use. These challenges require careful attention to ensure the successful integration of NLP technology into the construction field. In conclusion, these results testify to a growing recognition of the potential of NLP technology to meet the operational and informational challenges of the construction industry.

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