Abstract
Abstract. Correct and reliable identification and classification of different structures and infrastructures that make up a city (e.g. residential buildings, school buildings, hospitals, power stations, routes of communication, etc.) are of great importance for the AEC/FM (Architecture, Engineering, Construction, and Facilities Management) domain and for seismic risk assessments, among others. For decades, the method of collecting buildings information has been through field campaigns. This practice requires significant resources in terms of qualified engineers or architects to identify the geometry of the different elements that constitute the structure, building materials and construction processes. Nowadays, there are different geospatial techniques that allow data acquisition on a massive scale in a short period of time. In particular, by means of laser measurements, it is possible to have clouds of millions of points with geometric and radiometric information in a matter of seconds. In this article, we present ABM-indoor, a LIDAR-based approach that automatically provides a three-dimensional models of buildings in vector format. Models include floors, ceilings, walls (up to five dominant directions), columns, elements located on floors and elements hanging from ceilings. Efforts are underway to transfer this model to a Building Information Model (BIM).
Highlights
Over the last decade, the demand for digital twins has increased considerably in different research fields, such as AEC/FM, earthquake engineering, cadastre and urban planning, among others
In order to provide an automated and consistent approach to information processing and to eliminate the shortcomings of extensive field campaigns, we have developed a method that complements existing approaches for obtaining digital indoor and outdoor models of buildings, and Building Information Models (BIMs)
We present As-Built Model (ABM)-indoor, an approach to automatically classify and model unorganized and organized point clouds
Summary
The demand for digital twins has increased considerably in different research fields, such as AEC/FM, earthquake engineering, cadastre and urban planning, among others. The cadastral data is often not complete and falls short of the minimum required information to create reliable structural models This is especially true for older buildings in the developed parts of the world. In most cases, non-structural and content elements, which are a major source of economic losses in case of strong earthquakes, in the low seismic hazard regions (Torres et al, 2019), are omitted This leads to uncertainties in the results obtained. In order to provide an automated and consistent approach to information processing and to eliminate the shortcomings of extensive field campaigns, we have developed a method that complements existing approaches for obtaining digital indoor and outdoor models of buildings, and Building Information Models (BIMs).
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