Publications / 2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada

Enabling BIM for Property Management of Existing Buildings Based on Automated As-is Capturing

Ralf Becker, Elisa Lublasser, Jan Martens, Raymond Wollenberg, Haowei Zhang, Sigrid Brell-Cokcan and Jörg Blankenbach
Pages 201-208 (2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada, ISBN 978-952-69524-0-6)

Digitization and automation in construction are increasing particularly due to the establishment of Building Information Modelling (BIM). The models of BIM contain geometric as well as semantic information. The level of abstraction ranges from coarse models up to detailed modeled technical components of the buildings. So far, BIM has been developed and used for the planning and construction phase of the building’s lifecycle. In order to fully use the benefits of BIM also for the operation and refurbishment phase, BIM models need to provide a reliable data basis of the as-built and respectively the as-is situation. However, up to now many properties have neither been planned nor constructed using BIM, at times not even digital planning information is available. Therefore, the digital model must be created from the real world. The author’s research proposes the development of an automated as-is capturing process of existing buildings as well as the data integration into BIM as a basis for property management. Suitable capturing techniques have been analyzed. Up to now, these techniques and the subsequent data transfer are still characterized by lots of manual work. Accelerating this process requires methods for the automation of data segmentation, classification and the modeling process. Conventional data capturing techniques such as laser scanning measure only visible surfaces. However, knowledge about inbuilt materials, constructional layers or thickness of e.g. walls is also important for optimized planning and utilization. This paper summarizes the results of a joint research project in cooperation with a property management company.

Keywords: Building Information Modeling, BIM, Automation and Robotics, Data Sensing, Computing