Tracking of secondary and temporary objects in structural concrete work

Previous research has shown that “Scan-vs-BIM ” object recognition systems, that fuse 3D point clouds from Terrestrial Laser Scanning (TLS) or digital photogrammetry with 4D project BIM, provide valuable information for tracking structural works. However, until now, the potential of these systems has been demonstrated for tracking progress of permanent structures only; no work has been reported yet on tracking secondary or temporary structures. For structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. Together, they constitute most of the earned value in concrete work. The impact of tracking such elements would thus be added veracity and detail to earned value calculations, and subsequently better project control and performance. This paper presents three different techniques for recognizing concrete construction secondary and temporary objects in TLS point clouds. Two of the techniques are tested using real-life data collected from a reinforced concrete building construction site. The preliminary experimental results show that it is feasible to recognize secondary and temporary objects in TLS point clouds with good accuracy; but it is envisaged that superior results could be achieved by using additional cues such colour and 3D edge information

An Integrated Scan-to-BIM Approach for Buildings Energy Performance Evaluation and Retrofitting

Energy retrofitting is paramount to reduce the use of energy in existing buildings, with benefits to the environment and people’s economy. The increasing use of novel technologies and innovative methodologies, such as Terrestrial Laser Scanning (TLS) and Building Information Modelling (BIM), is contributing to optimise retrofit processes. In the context of energy efficiency retrofitting, complex semantic 3D BIM models are required that include specific information, such as second level space boundaries (2LSBs), material energy performance properties, and information of the Heating Ventilation and Air Conditioning (HVAC) system and their layout. All this information is necessary for energy analysis of the existing building and planning of effective retrofitting strategies. In this paper, we present an integrated (semi-)automated Scan-to-BIM approach to produce BIM models from point clouds and photographs of buildings by means of computer-vision and artificial intelligence techniques, as well as a Graphical User Interface (GUI) that enables the user to complete the models with information that cannot be retrieved by means of visual features. Information about the materials and their performance properties as well as the specification of the HVAC component is obtained from a database that integrates information from BAUBOOK, OKOBAUDAT and ASHRAE. The Scan-to-BIM tool introduced in this paper is evaluated with data from an inhabited two-storey building, delivering promising results in energy simulations

Model and data management issues in the integrated assessment of existing building stocks

The increasing population growth and urbanization rises the worldwide consumption of material resources and energy demand. The challenges of the future will be to provide sufficient resources and to minimize the continual amount of waste and energy demand. For the achievement of sustainability, increasing recycling rates and reuse of materials, next to the reduction of energy consumption has the highest priority. This article presents the results of the multidisciplinary research project SCI_BIM, which is conducted on an occupied existing building. Within SCI_BIM, a workflow for coupling digital technologies for scanning and modeling of buildings is developed. Laser scanning is used for capturing the geometry, and ground-penetrating radar is used for assessing material composition. For the semi-automated generation of an as-built BIM, algorithms are developed, wherefore the Point-Cloud serves as a basis. The BIMmodel is used for energy modeling and analysis as well as for the automated compilation of Material Passports. Further, a gamification concept will be developed to motivate the buildings’ users to collect data. By applying the gamification concept, the reduction of energy consumption together with an automated update of the as-built BIM will be tested. This article aims to analyze the complex interdisciplinary interactions, data, and model exchange processes of various disciplines collaborating within SCI_BIM. Results show that the developed methodology is confronted with many challenges. Nevertheless, it has the potential to serve as a basis for the creation of secondary raw materials cadaster and for the optimization of energy consumption in existing buildings

On systematic approaches for interpreted information transfer of inspection data from bridge models to structural analysis

In conjunction with the improved methods of monitoring damage and degradation processes, the interest in reliability assessment of reinforced concrete bridges is increasing in recent years. Automated imagebased inspections of the structural surface provide valuable data to extract quantitative information about deteriorations, such as crack patterns. However, the knowledge gain results from processing this information in a structural context, i.e. relating the damage artifacts to building components. This way, transformation to structural analysis is enabled. This approach sets two further requirements: availability of structural bridge information and a standardized storage for interoperability with subsequent analysis tools. Since the involved large datasets are only efficiently processed in an automated manner, the implementation of the complete workflow from damage and building data to structural analysis is targeted in this work. First, domain concepts are derived from the back-end tasks: structural analysis, damage modeling, and life-cycle assessment. The common interoperability format, the Industry Foundation Class (IFC), and processes in these domains are further assessed. The need for usercontrolled interpretation steps is identified and the developed prototype thus allows interaction at subsequent model stages. The latter has the advantage that interpretation steps can be individually separated into either a structural analysis or a damage information model or a combination of both. This approach to damage information processing from the perspective of structural analysis is then validated in different case studies

Building Information Modeling (BIM) Utilization for 3D Fiscal Cadastre

Parcels data in Indonesia are still stored in 2-dimensional (2D) geometry which are integrated with other attribute data, such as the case with the Directorate of Land and Building Tax Indonesia. Whereas, building taxes assessment refers to a number of details that require the information to be stored in 3-dimensional (3D) forms. This study aims at the use of Building Information Modeling (BIM) technology, which widely used in building asset management in 3D. This research illustrates the usability of the role of BIM in assessing and managing building taxes in Indonesia. The point clouds were obtained using Terrestrial Laser Scanner (TLS) technology. The point clouds processed so that it can form 3-dimensional geometrical apartment. The attributes of the 3-dimensional model integrated with the geometric model using the BIM concept. The results analyzed to assess whether BIM concept was able to fulfill the needs of the 3D fiscal cadastre in Indonesia

Planning for scanning in construction : optimizing 3D laser scanning operations using building information modelling and a novel specification on surface scanning completeness.

Application of Terrestrial Laser Scanning (TLS) technology in the Architectural Engineering and Construction (AEC) industry is gaining popularity because the technology uniquely offers the means to create as-built three-dimensional (3D) models of existing facilities, and conduct construction project progress and dimensional quality measurements. An open challenge with regard to the use TLS for such applications is to efficiently generate effective scanning plans that satisfy pre-defined point cloud quality specifications. Two such specifications are currently commonly used: Level of Accuracy (LOA) that focuses on individual point precision, and Level of Detail (LOD) that focuses on point density. Given such specifications, current practice sees professionals manually prepare scanning plans using existing 2D CAD drawings, some ad-hoc rules (of thumb), and their experience. Yet, it is difficult to manually generate and analyse laser scanning plans to ensure they satisfy scanning quality specifications such as those above. Manually-defined plans may easily lead to over-scanning, or worse under-scanning with incomplete data (which may require the team to go back on site to acquire complementary data). To minimize the risk of producing inadequate scanning plans, some semi-automated and automated methods have been proposed by researchers that use the 3D (BIM) model generated during the design stage. These methods take consideration for LOA and LOD. However, these are point-based specifications that do not guarantee that a sufficient amount of the surface of each object is covered by the acquired data, despite this aspect being important to many of the applications for which TLS is employed (e.g. modelling existing facilities). Therefore, this research uniquely proposes a novel planning for scanning quality specification, called Level of Surface Completeness (LOC) that assesses point cloud quality in terms of surface completeness. In addition, an approach is proposed for automatic planning for scanning in the AEC industry that takes both LOA and LOC specifications into account. The approach is ‘generic’ in the sense that it can be employed for any type of project. It is designed to generate automatic laser scanning plans using as input: (1) the facility’s 3D BIM model; (2) the scanner’s characteristics; and (3) the LOA and LOC specifications. The output is the smallest set of scanning locations necessary to achieve those requirements. The optimal solution is found by formulating the problem as a binary integer programming optimization problem, which is easily solved using a branch-and-cut algorithm. To assess the performance of the approach, experiments are conducted using a simple concrete structural model, a more complex structural model, and a section of the latter extended with Mechanical Electrical and Plumbing (MEP) components. The overall performance of the proposed approach for automatic planning for scanning is encouraging, showing that it is possible to take surface-based specifications into account in automated planning-for-scanning algorithms. However, the experimental results also highlight a significant weakness of the approach presented here which is that it does not take into account the overlapping of surfaces covered from different scanning locations and thus may inaccurately assess covered surfaces