Optimizing construction processes and improving building performance through data engineering and computation

Abstract

The use of manual labour and physically demanding building techniques is a hallmark of the construction industry. However, recent technological developments have given rise to a rising tendency in the construction industry towards digitalization and data-driven decision-making. The purpose of this study is to investigate how data engineering and computing are used in the construction sector and how they affect building methods. The study depends on a thorough analysis of the literature, which includes 26 pertinent papers from scholarly publications and business reports. The results imply that computing and data engineering can dramatically enhance building procedures and results. Particularly, these technologies make project planning, resource allocation, and risk management more precise and effective. The use of data can also result in more accountability and transparency in building projects, which can save costs and enhance overall project performance. The study also looks at the challenges involved in applying data engineering and computation in the construction sector, including problems with data security, privacy, and quality. The study also emphasises the requirement for more thorough data management plans as well as the creation of industry-wide standards and best practices. The results have important ramifications for experts in the field, academics, and decision-makers, and they can guide future initiatives to incorporate data-driven methods into the construction sector.