An approach for fusing data from multiple sources to support construction productivity monitoring

Existing research studies in construction management domain, such as productivity monitoring, cost estimation and project controls, have utilized multi-source data fusion to support various types of project management decisions. Multi-source data fusion is referred to a process of fusing data from multiple heterogeneous data sources. Data fusion approaches incorporated in the existing research studies within construction management domain are specific to a given task, such as labour productivity monitoring and defect detection. As a result, these data fusion approaches do not necessarily support tasks other than the ones they are designed for. In this paper, the authors describe a new multi-source data fusion approach to support construction productivity monitoring. The developed approach addresses the challenges associated with capturing dynamic user queries, identifying relevant data sources from a given set of available data sources, generating and executing correct sequence of steps to fuse relevant data sources to answer a given user query. A prototype system was developed to validate the generality of the approach based on the representative queries from construction project engineers, which are identified based on previous research studies.