ConXR: A Comparative Participatory Platform for Construction Progress Monitoring

• Published in: Journal of the Institution of Engineers (India). Series A, Civil, architectural, environmental and agricultural Engineering Vol. 105; no. 2; pp. 249 - 259
• Main Authors: Sindhu Pradeep, Megha, Reja, Varun Kumar, Varghese, Koshy
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 2024
• Subjects: Civil Engineering; Engineering; Original Contribution; Extended reality; Construction automation; Comparative analysis; Building information modelling; Progress monitoring; Construction management
• ISSN: 2250-2149; 2250-2157
• DOI: 10.1007/s40030-024-00799-0

Existing progress monitoring systems in the construction industry rely heavily on manual data entry and have limited visualization capabilities. Although several researchers have attempted to address these deltas through various automated technologies, their practical implementation in sites has not reached its full potential. This could be achieved through easy-to-implement platforms that facilitate automated data capture and visual representation of progress, thereby providing a better understanding of the project status and facilitating improved project controls. Furthermore, features to visualize the performance of multiple crews will enable comparative analysis and establish improved benchmarks for the project goals. ConXR, a platform that integrates automated data capture, an extended reality environment for progress visualization, and comparative participant analysis, is proposed. ConXR is designed to be a structured platform that displays as-planned and as-built models generated from the automatically acquired data. In ConXR, crews are designated as the players within a competitive environment to enable comparative performance assessment in each construction stage. The architecture and development details of the platform are presented, along with an illustration of its application. The interactive features of ConXR have the potential to establish and achieve improved progress targets based on preceding crew performances. Furthermore, ConXR can enable immersive progress visualization of automatically acquired data as digital models. The novelty of ConXR lies in its comparative participatory features that enable crew performance evaluation by engaging them in an environment where constraints and their impacts are documented in a structured form.