Visualization in Engineering 

About: Visualization in Engineering is an academic journal. The journal publishes majorly in the area(s): Building information modeling & Visualization. It has an ISSN identifier of 2213-7459. Over the lifetime, 80 publications have been published receiving 2181 citations.

Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works

Abstract: Over the past few years, the application of camera-equipped Unmanned Aerial Vehicles (UAVs) for visually monitoring construction and operation of buildings, bridges, and other types of civil infrastructure systems has exponentially grown. These platforms can frequently survey construction sites, monitor work-in-progress, create documents for safety, and inspect existing structures, particularly for hard-to-reach areas. The purpose of this paper is to provide a concise review of the most recent methods that streamline collection, analysis, visualization, and communication of the visual data captured from these platforms, with and without using Building Information Models (BIM) as a priori information. Specifically, the most relevant works from Civil Engineering, Computer Vision, and Robotics communities are presented and compared in terms of their potential to lead to automatic construction monitoring and civil infrastructure condition assessment.

Machine learning for estimation of building energy consumption and performance: a review

Abstract: Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy efficiency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most effective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy efficiency at a very early design stage. On the other hand,efficient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, artificial intelligence (AI) in general and machine learning (ML) techniques in specific terms have been proposed for forecasting of building energy consumption and performance. This paper provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance.

Low-cost virtual reality environment for engineering and construction

Abstract: Presenting significant building or engineering 3D-models is a crucial part of the planning, construction and maintenance phases in terms of collaboration and understanding. Especially in complex or large-scale models, immersion is one of the major key factors for being able to intuitively perceive all aspects of the scene. A fully immersive system needs to give the user a large field-of-view with reduced latency for lifelike impression. Technologies such as VRwalls and shutter glasses can deliver high refresh rates, yet fail to give a large field-of-view. Head-mounted-devices for virtual reality fill this gap. Head tracking mechanisms translate movements of the user’s head into virtual camera movements and enable a natural way of examining models. Unlike a stereoscopic representation with projectors, point-of-view tracking can be achieved separately for each individual user. Hardware costs for such systems were very high in the past, but have dropped due to virtual reality systems now gaining traction in the mainstream gaming community. In this paper we present a way to build a low-cost, highly immersive virtual reality environment for engineering and construction applications. Furthermore, we present a method to simplify and partly automate the process of reusing digital building models, which are already used in construction, to create virtual scenes, instead of having to do parallel content creation for visualization. Using the Oculus Rift head-mounted display and the Leap Motion hand-tracking device, we show the possibilities of naturally interacting within a virtual space in different use cases. The software, based on the popular game engine Unreal Engine 4, will be used as a basis for further research and development. Building Information Modeling data can be imported to UE4 with our presented plugin. Using an automated database for mapping materials to the geometry simplifies the process of importing Building Information Modeling entities. The refresh rate of the system stays within acceptable margins needed for virtual reality applications using head-mounted devices. Head-mounted devices present a great potential for the Architecture, Engineering and Construction industry, as a person can experience realistic first-person situations without having to care about injuries. Automated processes for the simplification of content creation, leveraging existing models, and the usage of visual programming languages enable even nonprogrammers to create scenarios to their needs.

High-precision vision-based mobile augmented reality system for context-aware architectural, engineering, construction and facility management (AEC/FM) applications

Abstract: Many context-aware techniques have been proposed to deliver cyber-information, such as project specifications or drawings, to on-site users by intelligently interpreting their environment. However, these techniques primarily rely on RF-based location tracking technologies (e.g., GPS or WLAN), which typically do not provide sufficient precision in congested construction sites or require additional hardware and custom mobile devices. This paper presents a new vision-based mobile augmented reality system that allows field personnel to query and access 3D cyber-information on-site by using photographs taken from standard mobile devices. The system does not require any location tracking modules, external hardware attachments, and/or optical fiducial markers for localizing a user’s position. Rather, the user’s location and orientation are purely derived by comparing images from the user’s mobile device to a 3D point cloud model generated from a set of pre-collected site photographs. The experimental results show that 1) the underlying 3D reconstruction module of the system generates complete 3D point cloud models of target scene, and is up to 35 times faster than other state-of-the-art Structure-from-Motion (SfM) algorithms, 2) the localization time takes at most few seconds in actual construction site. The localization speed and empirical accuracy of the system provides the ability to use the system on real-world construction sites. Using an actual construction case study, the perceived benefits and limitations of the proposed method for on-site context-aware applications are discussed in detail.

Review and analysis of augmented reality literature for construction industry

Abstract: Research has identified various beneficial capabilities for augmented reality technologies in the AEC industry such as virtual site visits, comparing as-built and as-planned status of projects, pre-empting schedule disputes, enhancing collaboration opportunities, and planning/training for similar projects. This paper provides an expanded foundation for future research by presenting a statistical review of augmented reality technology in the AEC industry. The review is based on articles found within eight well-known journals in architecture, engineering, construction, and facility management (AEC/FM) until the end of the year 2012. The review further narrows the literature within these journals by considering only those 133 articles found through a key word search for “augmented reality.” The selected journal articles are classified within the following dimensions: improvement focus, industry sector, target audience, project phase, stage of technology maturity, application area, comparison role, and technology. The number of articles within these dimensions are used to identify maturing and emerging trends in the literature as well as to synthesize the current state-of-the-art of augmented reality research in the AEC industry. In summary, the AR literature has increasingly focused on the demonstration of visualization and simulation applications for comparison of as-planned versus as-built statuses of the project during the construction phase to monitor project progress and address issues faced by field workers. In addition, the future trend is toward using web-based mobile augmented systems for field construction monitoring.