NATURAL LANGUAGE PROCESSING APPROACH FOR AUTOMATED BILL OF QUANTITIES PREPARATION.

ABSTRACT

The preparation of Bills of Quantities (BOQ) in the construction industry is a critical task that traditionally involves significant manual effort and is prone to errors. This project explores the application of Natural Language Processing (NLP) to automate the BOQ preparation process, aiming to enhance accuracy and efficiency while reducing the time and labor associated with manual methods. The study developed and evaluated an NLP-based tool designed to generate BOQs that adhere to the Building Engineering Standard Method of Measurement (BESMM). Through a combination of quantitative and qualitative research methods, the tool's performance was assessed against traditional practices. The findings indicate that the NLP tool significantly improves the speed of BOQ preparation and reduces errors by automating data extraction and computation. However, challenges related to full compliance with BESMM standards and integration with existing project management systems were identified. The study recommends further development of the NLP algorithms, improvements in the tool’s integration capabilities, and ongoing user support to facilitate wider adoption. This research contributes to the body of knowledge in construction project management by demonstrating the feasibility and benefits of using NLP for BOQ preparation. It also lays the groundwork for future studies to explore advanced applications of NLP in construction and other industries, promoting the broader adoption of AI-driven automation tools.