TY - GEN
T1 - A framework for model-driven acquisition and analytics of visual data using UAVs for automated construction progress monitoring
AU - Lin, Jacob J.
AU - Han, Kevin K.
AU - Golparvar-Fard, Mani
N1 - Publisher Copyright:
© 2015 ASCE.
PY - 2015
Y1 - 2015
N2 - Automated assessment of work-in-progress using large collections of site images and 4D BIM has potential to significantly improve the efficiency of construction project controls. Nevertheless, today's manual procedures for taking site photos do not support the desired frequency or completeness for automated progress monitoring. While the usage of Unmanned Aerial Vehicles for acquisition of site images has gained popularity, their application for addressing issues associated with image-based progress monitoring and particularly leveraging 4D BIM for steering the data collection process has not been investigated before. By presenting examples from two case studies conducted on real-world construction projects, this paper suggests a framework for model-driven acquisition and analytics of progress images. In particular, the potential of spatial (geometry, appearance, and interconnectivity) and temporal information in 4D BIM for autonomous data acquisition and analytics that guarantees completeness and accuracy for both as-built modeling and monitoring work-in-progress at the schedule task-level is discussed.
AB - Automated assessment of work-in-progress using large collections of site images and 4D BIM has potential to significantly improve the efficiency of construction project controls. Nevertheless, today's manual procedures for taking site photos do not support the desired frequency or completeness for automated progress monitoring. While the usage of Unmanned Aerial Vehicles for acquisition of site images has gained popularity, their application for addressing issues associated with image-based progress monitoring and particularly leveraging 4D BIM for steering the data collection process has not been investigated before. By presenting examples from two case studies conducted on real-world construction projects, this paper suggests a framework for model-driven acquisition and analytics of progress images. In particular, the potential of spatial (geometry, appearance, and interconnectivity) and temporal information in 4D BIM for autonomous data acquisition and analytics that guarantees completeness and accuracy for both as-built modeling and monitoring work-in-progress at the schedule task-level is discussed.
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U2 - 10.1061/9780784479247.020
DO - 10.1061/9780784479247.020
M3 - Conference contribution
AN - SCOPUS:84936872871
T3 - Congress on Computing in Civil Engineering, Proceedings
SP - 156
EP - 164
BT - Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering
A2 - O'Brien, William J.
A2 - Ponticelli, Simone
PB - American Society of Civil Engineers
T2 - 2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015
Y2 - 21 June 2015 through 23 June 2015
ER -