Progressive Site Modelling with Videogrammetry

A number of methods are commonly used today to collect as-built spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic and cost-efficient at the same time. LiDARmethods generate high resolution depth information, but the significant cost of the equipment counteracts their benefits for the majority of construction projects. This is true especially for small projects, where projected savings hardly justify adopting this technology. Vision-based technologies, such as videogrammetry, is potentially able to address the existing limitations.

Content Based Integration of Construction Site Images in Architecture, Engineering, Construction, and Facilities Management (AEC/FM) Model based Systems

This book explores the processes for retrieval, classification, and integration of construction images in AEC/FM model based systems. The author describes a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval that have been integrated into a novel method for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks. objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Three-Dimensional Tracking of Construction Resources using an On-Site Camera System

Vision trackers have been proposed as a promising alternative for tracking at large-scale, congested construction sites. They provide the location of a large number of entities in a camera view across frames. However, vision trackers provide only two-dimensional (2D) pixel coordinates, which are not adequate for construction applications. This paper proposes and validates a method that overcomes this limitation by employing stereo cameras and converting 2D pixel coordinates to three-dimensional (3D) metric coordinates. The proposed method consists of four steps: camera calibration, camera pose estimation, 2D tracking, and triangulation. Given that the method employs fixed, calibrated stereo cameras with a long baseline, appropriate algorithms are selected for each step. Once the first two steps reveal camera system parameters, the third step determines 2D pixel coordinates of entities in subsequent frames. The 2D coordinates are triangulated on the basis of the camera system parameters to obtain 3D coordinates. The methodology presented in this paper has been implemented and tested with data collected from a construction site. The results demonstrate the suitability of this method for on-site tracking purposes.

Shape-Based Retrieval of Construction Site Photographs

Digital photographs of construction site activities are gradually replacing their traditional paper based counterparts. Existing digital imaging technologies in hardware and software make it easy for site engineers to take numerous photographs of “interesting” processes and activities on a daily basis. The resulting photographic data are evidence of the “as-built” project, and can therefore be used in a number of project life cycle tasks. However, the task of retrieving the relevant photographs needed in these tasks is often burdened by the sheer volume of photographs accumulating in project databases over time and the numerous objects present in each photograph. To solve this problem, the writers have recently developed a number of complementary techniques that can automatically classify and retrieve construction site images according to a variety of criteria (materials, time, date, location, etc.). This paper presents a novel complementary technique that can automatically identify linear (i.e., beam, column) and nonlinear (i.e., wall, slab) construction objects within the image content and use that information to enhance the performance of the writers’ existing construction site image retrieval approach.

Long Distance Wireless Networking for Site - Office Data Communications

Effective data communications between the project site and decision making office can be critical for the success of a construction project. It allows convenient access to centrally stored information and allows centrally located decision makers to remotely monitor the site and collect data in real-time. However, high bandwidth, flexible data communication networks, such as wired local area networks, can often be time-consuming and costly to deploy for such purposes especially when project sites (dams, highways, etc.) are located in rural, undeveloped areas where networking infrastructure is not available. In such construction sites, wireless networking could reliably link the construction site and the decision-making office. This paper presents a case study on long-distance, site – office wireless data communications. The purpose was to investigate the capability of wireless technology in exchanging construction data in a fast and efficient manner and in allowing site personnel to interact and share knowledge and data with the office staff. This study took place at the University of Michigan’s campus where performance, reliability, and cost/benefit tests were performed. The indoor and outdoor tests performed demonstrated the suitability of this technology for office-site data communications and exposed the need for more research to further improve the reliability and data handling of this technology.

Automated On-Site Retrieval of Project Information

Among several others, the on-site inspection process is mainly concerned with finding the right design and specifications information needed to inspect each newly constructed segment or element. While inspecting steel erection, for example, inspectors need to locate the right drawings for each member and the corresponding specifications sections that describe the allowable deviations in placement among others. These information seeking tasks are highly monotonous, time consuming and often erroneous, due to the high similarity of drawings and constructed elements and the abundance of information involved which can confuse the inspector. To address this problem, this paper presents the first steps of research that is investigating the requirements of an automated computer vision-based approach to automatically identify “as-built” information and use it to retrieve “as-designed” project information for field construction, inspection, and maintenance tasks. Under this approach, a visual pattern recognition model was developed that aims to allow automatic identification of construction entities and materials visible in the camera’s field of view at a given time and location, and automatic retrieval of relevant design and specifications information.

Material-Based Construction Site Image Retrieval

The technological advancements in digital imaging, the widespread popularity of digital cameras, and the increasing demand by owners and contractors for detailed and complete site photograph logs have triggered an ever-increasing growth in the rate of construction image data collection, with thousands of images being stored for each project. However, the sheer volume of images and the difficulties in accurately and manually indexing them have generated a pressing need for methods that can index and retrieve images with minimal or no user intervention. This paper reports recent developments from research efforts in the indexing and retrieval of construction site images in architecture, engineering, construction, and facilities management image database systems. The limitations and benefits of the existing methodologies will be presented, as well as an explanation of the reasons for the development of a novel image retrieval approach that not only can recognize construction materials within the image content in order to index images, but also can be compatible with existing retrieval methods, enabling enhanced results.

Improving the superconducting properties of single grain Sm-Ba-Cu-O bulk superconductors fabricated in air by increased control of Sm/Ba substitution effects

The extreme sensitivity of Sm/Ba at high temperature in air becomes an obstacle to the fabrication of SmBCO single grains that exhibit stable and reliable superconducting properties. In this research, the superconducting properties of SmBCO single grains fabricated by top seeded melt growth (TSMG) from different batches of commercial SmBa2Cu3O 7-d (Sm-123) precursor powder using different processing atmospheres (air and 0.1% O2 in Ar), different processing methods (isothermal growth and continuous cooling) and different amounts of BaO2 content to suppress Sm/Ba substitution in air have been investigated in an attempt to understand fully the TSMG process for this system. As a result, based on extensive data, a novel and simple, low temperature post-annealing approach is proposed specifically to overcome the sensitivity of Tc to Sm/Ba substitution in order to simplify the fabrication of SmBCO and to increase its reliability with a view to the practical processing of these materials. Initial processing trials have been performed successfully to demonstrate the viability of the novel post-annealing process. © 2013 IOP Publishing Ltd.

Assessing effects of site characteristics on remediation secondary life cycle impact with a generalised framework

The 'sustainable remediation' concept has been broadly embraced by industry and governments in recent years in both the US and Europe. However, there is a strong need for more research to enhance its 'practicability'. In an attempt to fill this research gap, this study developed a generalised framework for selecting the most environmentally sustainable remedial technology under various site conditions. Four remediation technologies were evaluated: pump and treat (P&T), enhanced in situ bioremediation (EIB), permeable reactive barrier (PRB), and in situ chemical reduction (ISCR). Within the developed framework and examined site condition ranges, our results indicate that site characteristics have a profound effect on the life cycle impact of various remedial alternatives, thus providing insights and valuable information for determining what is considered the most desired remedy from an environmental sustainability perspective. © 2014 © 2014 University of Newcastle upon Tyne.