Planning-Based Approach for Fusing Data from Multiple Sources for Construction Productivity Monitoring

Abstract

Project management tasks, such as productivity monitoring and cost estimation, require data to be fused from multiple data sources. Data fusion approaches incorporated in the existing research studies within the construction management domain support a specific task or a decision (e.g., labor productivity monitoring or defect detection). Hence, most of the previously developed approaches do not necessarily support tasks other than the ones that they were intended for. This paper describes an automated planning approach as a general way to fuse data from multiple sources to support construction productivity monitoring tasks. A prototype system, which incorporates two planning algorithms, was developed to validate the generality of the approach on the basis of representative queries of construction engineers and managers identified in previous research studies.