ITR/IM+AP Early Defect Detection and Management at Construction Sites Using Integrated Project Models, Laser Scanners and Embedded Sensor Systems

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

The construction industry suffers from costly remedies associated with late defect detection at construction sites. Frequent and accurate assessment of the status of work-in-place, identifying critical spatio-temporal and quality related deviations, and predicting the impacts of these deviations during a construction project are necessary for active project control and for developing an accurate project history. This research project builds on, combines and extends the advances in generating 3D environments using laser scanners, collecting quality information about built environments using embedded sensors, and generation and utilization of semantically-rich Architecture/Engineering/ Construction (A/E/C) project models, in developing an integrated early defect detection system. The research objectives include: (1) formulating strategies/mechanisms to utilize laser scanning and embedded sensor systems for frequent and accurate collection and representation of spatial and quality related as-built data, (2) developing mechanisms for integrating and interpreting data acquired from these systems with the project model, (3) developing a general, flexible and integrated representation schema to model product, process and as-built information, and (4) formalizing mechanisms for automated defect detection and management. The expected contributions of this research fall within the fields of robotics, embedded sensing in civil engineering, A/E/C project modeling and analysis. The societal impacts of this research include potential savings in rework and maintenance costs.