Paper Title
IMPLEMENTATION OF AI-ENHANCED PARAMETRIC MODELLING FOR LARGE CONSTRUCTION PROJECT: A CASE STUDY

Abstract
In civil large projects, the challenge of large data handling is paramount, necessitating sophisticated approaches to resource optimization. These projects operate within dynamic situations where variables can change rapidly, requiring real-time data analysis and decision-making capabilities. The development of Artificial Intelligence (AI), particularly through deep learning and advanced computing systems, has revolutionized data analysing processes. By leveraging these technologies, project managers can simulate various scenarios, process the vast amounts of data involved in large projects, and do so in the least time and at the least cost. This proactive approach ensures that resources are optimized, costs are controlled, and project timelines are adhered to, ultimately contributing to the successful completion of these complex undertakings. In this case study focusing on large projects, the piling activity has been scrutinized due to frequent delays caused by improper selection and deployment of equipment. This Large project under review involves handling large data sets, including details of nearly 5,000 piles, 32,000 variations in soil strata, and 93,000 hours of equipment productivity, alongside comprehensive cost details. By employing multi-linear regression analysis, the relationship between soil strata, machinery, and pile cycle time is examined, facilitating data formulation for informed decision-making. The analysed data, enabling stakeholders to derive an optimum solution that minimizes both time and cost. Furthermore, this model has been validated in existing projects, and the results have been satisfactory. This approach is crucial in managing the dynamic situations inherent in such large-scale projects, ensuring efficient and timely project completion. The use of AI in civil engineering is still limited, but it has huge potential, especially in large-scale infrastructure projects. AI can tackle the complex challenges of these kind of projects by streamlining processes, optimizing resource allocation, and improving decision-making. This integration of AI boosts efficiency throughout all project phases, from planning to maintenance, and improves outcomes within time and budget limits. Keywords - Artificial Intelligence, Civil Engineering, Big Data, Deep Learning, Multi Linear Regression Algorithms.