Point-Cloud-Based Structural Health Monitoring and Quality Control for Complex Heritage Morphologies

Heritage buildings often exhibit complex, irregular, and evolving geometries, making traditional inspection and monitoring methods inadequate. With the rapid improvement of terrestrial laser scanning, photogrammetry, and LiDAR technologies, point clouds offer unprecedented opportunities for digitally capturing full-shape geometry and tracking changes over time. This PhD project will develop advanced computational methods for automated analysis, comparison, and interpretation of large-scale point cloud datasets, enabling high-precision health monitoring, deformation tracking, and quality control for heritage buildings. The research will explore the unique challenges of heritage structures, including irregular morphologies, partial visibility, environmental constraints, and historical preservation requirements. Research Goals: 1) Develop algorithms to detect, classify, and quantify shape changes, deformation, or damage from multi-temporal point clouds. 2) Design automated workflows for scan-vs-BIM, scan-vs-scan, and multi-scan comparison of complex architectural heritage. 3) Explore machine learning or geometric computing approaches for pattern recognition and anomaly detection. 4) Create robust metrics and digital protocols for heritage condition assessment and conservation decision-making. 94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021

The standard University IELTS English language requirement is 6.5 overall with 6.0 in each individual element (reading, writing, listening and speaking).

International students: £29,500

UK students: £5,238

UK/Home: £5,238

International: £29,500

October 2026, February 2027, July 2027

31 December 2026

• Loughborough, United Kingdom