AI-COMPLI: Project Proposal

This project proposes the utilisation of computer vision and machine learning in combination with camera technology to enhance the process of visual inspection in construction environments.

At present, on-site camera technology is primarily deployed for purposes such as progress tracking, security, health and safety monitoring, and operational oversight. While these applications provide valuable raw data, the information captured is not consistently converted into actionable insights that can directly support decision-making on site.

Through the integration of reality capture methods, this research aims to identify potential issues at an early stage and prompt further evaluation, enabling a more proactive approach to site management and defect prevention. Importantly, the solution will be designed as a human-in-the-loop system, ensuring that automated detection and analysis are combined with expert judgment rather than replacing it.

The project is inherently interdisciplinary, drawing on expertise from both the construction domain and the fields of data science and artificial intelligence. By combining these perspectives, the research seeks to develop tools that are both technologically robust and practically relevant for on-site application.

Furthermore, the initiative will be supported by industry expertise from Fenagh Engineering & Testing, providing valuable insights from practitioners who understand the realities of construction processes and quality assurance. This collaboration is intended to ground the research in real-world challenges and ensure its outcomes are directly applicable to industry needs.