Ambasana Hetvi Girishbhai

CM4050

PCM21135

This research study aims to explore the potential benefits of integrating machine learning in the LPS by developing a framework to identify constraints affecting the project. The study seeks to evaluate the accuracy and effectiveness of machine learning models in predicting and managing lookahead constraints of construction projects by analyzing structured and unstructured data from LPS schedules and constraint analysis. The study's findings can help construction companies to streamline workflows, increase efficiency, reduce errors, and improve the overall quality of construction projects.


Report Content

Introduction

Introduction

Literature Review

Literature Review

Research Methodology

Data Collection

Data Analysis

Data Analysis

Data Analysis

Conclusion and Future Scope of the Study