Developing a BIM-Based Asset Management Framework for Urban Infrastructures

Abstract

Infrastructure asset management needs extensive data collection to create a comprehensive inventory record that consolidates pertinent asset details, encompassing their operational and maintenance activities in an integrated manner. Conventionally, the initial assessment involves a laborious, tedious, and expensive random walkthrough visual inspection. Using a case study of a station from the Bus Rapid Transit (BRT) Peshawar, this study explores the use of laser scanning as an alternative to manual inspection, employing Scan-to-BIM for asset management of infrastructures. The station's façade details at two different time intervals were laser-scanned to view the parametric details and geometrical features of its components and their physical condition in a virtual environment. Following validation of the scanned data through field inspection for accuracy and reliability, the data was utilized to develop semantic 3D models of the station with realistic geometries and dimensions. These models represent the as-is state of the assets covering the temporal geometrical changes in the form of added, deducted, or degraded elements as highlighted from the comparison of the successive models. Consequently, an intelligent and efficient 3D inventory and geometrical change detection system emerged, offering a viable substitute for traditional inventorying and data collection techniques.