ABSTRACT
The construction process is usually characterized by delays, deviations and rescheduling. An efficient control of the construction process requires a timely and continuous detection of the construction status and possible deviations. Subsequently, the construction progress should be analyzed quickly and in detail. As a result, responses to emerging issues and rescheduling can be performed timely. Currently, such adaptation is a mostly manual procedure, which is labor-intensive and time-consuming. This contribution examines the possibility of an intelligent adaptation of 4D models for construction scheduling by using pattern recognition methods. The primary focus is on the reducing of manual intervention and improving of progress monitoring.
