The interaction of lean and building information modeling in construction

Lean construction and Building Information Modeling are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, fifty-six interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete, but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers and developers of IT systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies

Architectural and Urban Spatial Digital Simulations

This study concerns digital tools and simulation methods necessary for the description, conception, perception, and analysis of spatial architectural and urban design. The purpose of the study is to categorize, analyse, and describe the influence of digital simulation tools and methods in architectural and urban design. The study analyses techniques, applications, and research in the field of digital simulations of architectural/urban ensembles while also referring to the benefits of their use both at the level of scientific and spatial perception of architectural/urban design

Towards a semantic Construction Digital Twin: directions for future research

As the Architecture, Engineering and Construction sector is embracing the digital age, the processes involved in the design, construction and operation of built assets are more and more influenced by technologies dealing with value-added monitoring of data from sensor networks, management of this data in secure and resilient storage systems underpinned by semantic models, as well as the simulation and optimisation of engineering systems. Aside from enhancing the efficiency of the value chain, such information-intensive models and associated technologies play a decisive role in minimising the lifecycle impacts of our buildings. While Building Information Modelling provides procedures, technologies and data schemas enabling a standardised semantic representation of building components and systems, the concept of a Digital Twin conveys a more holistic socio-technical and process-oriented characterisation of the complex artefacts involved by leveraging the synchronicity of the cyber-physical bi-directional data flows. Moreover, BIM lacks semantic completeness in areas such as control systems, including sensor networks, social systems, and urban artefacts beyond the scope of buildings, thus requiring a holistic, scalable semantic approach that factors in dynamic data at different levels. The paper reviews the multi-faceted applications of BIM during the construction stage and highlights limits and requirements, paving the way to the concept of a Construction Digital Twin. A definition of such a concept is then given, described in terms of underpinning research themes, while elaborating on areas for future research

NiftyNet: a deep-learning platform for medical imaging

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this application requires substantial implementation effort. Thus, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on TensorFlow and supports TensorBoard visualization of 2D and 3D images and computational graphs by default. We present 3 illustrative medical image analysis applications built using NiftyNet: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. NiftyNet enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications.Comment: Wenqi Li and Eli Gibson contributed equally to this work. M. Jorge Cardoso and Tom Vercauteren contributed equally to this work. 26 pages, 6 figures; Update includes additional applications, updated author list and formatting for journal submissio

Construction safety and digital design: a review

As digital technologies become widely used in designing buildings and infrastructure, questions arise about their impacts on construction safety. This review explores relationships between construction safety and digital design practices with the aim of fostering and directing further research. It surveys state-of-the-art research on databases, virtual reality, geographic information systems, 4D CAD, building information modeling and sensing technologies, finding various digital tools for addressing safety issues in the construction phase, but few tools to support design for construction safety. It also considers a literature on safety critical, digital and design practices that raises a general concern about ‘mindlessness’ in the use of technologies, and has implications for the emerging research agenda around construction safety and digital design. Bringing these strands of literature together suggests new kinds of interventions, such as the development of tools and processes for using digital models to promote mindfulness through multi-party collaboration on safet

Integrated HBIM-GIS Models for Multi-Scale Seismic Vulnerability Assessment of Historical Buildings

The complexity of historical urban centres progressively needs a strategic improvement in methods and the scale of knowledge concerning the vulnerability aspect of seismic risk. A geographical multi-scale point of view is increasingly preferred in the scientific literature and in Italian regulation policies, that considers systemic behaviors of damage and vulnerability assessment from an urban perspective according to the scale of the data, rather than single building damage analysis. In this sense, a geospatial data sciences approach can contribute towards generating, integrating, and making virtuous relations between urban databases and emergency-related data, in order to constitute a multi-scale 3D database supporting strategies for conservation and risk assessment scenarios. The proposed approach developed a vulnerability-oriented GIS/HBIM integration in an urban 3D geodatabase, based on multi-scale data derived from urban cartography and emergency mapping 3D data. Integrated geometric and semantic information related to historical masonry buildings (specifically the churches) and structural data about architectural elements and damage were integrated in the approach. This contribution aimed to answer the research question supporting levels of knowledge required by directives and vulnerability assessment studies, both about the generative workflow phase, the role of HBIM models in GIS environments and toward user-oriented webGIS solutions for sharing and public use fruition, exploiting the database for expert operators involved in heritage preservation

Communication Analysis through Visual Analytics: Current Practices, Challenges, and New Frontiers

The automated analysis of digital human communication data often focuses on specific aspects such as content or network structure in isolation. This can provide limited perspectives while making cross-methodological analyses, occurring in domains like investigative journalism, difficult. Communication research in psychology and the digital humanities instead stresses the importance of a holistic approach to overcome these limiting factors. In this work, we conduct an extensive survey on the properties of over forty semi-automated communication analysis systems and investigate how they cover concepts described in theoretical communication research. From these investigations, we derive a design space and contribute a conceptual framework based on communication research, technical considerations, and the surveyed approaches. The framework describes the systems' properties, capabilities, and composition through a wide range of criteria organized in the dimensions (1) Data, (2) Processing and Models, (3) Visual Interface, and (4) Knowledge Generation. These criteria enable a formalization of digital communication analysis through visual analytics, which, we argue, is uniquely suited for this task by tackling automation complexity while leveraging domain knowledge. With our framework, we identify shortcomings and research challenges, such as group communication dynamics, trust and privacy considerations, and holistic approaches. Simultaneously, our framework supports the evaluation of systems and promotes the mutual exchange between researchers through a structured common language, laying the foundations for future research on communication analysis.Comment: 11 pages, 2 tables, 1 figur