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

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

A Comparative Evaluation of Green Stormwater Infrastructure Tools: Co-Benefits and Alternative Funding

Green Stormwater Infrastructure (GSI) is a complicated concept for the majority of the population due to complexities of the technologies and the dearth of research done on co-benefits offered by the multiple types of GSI. As GSI and its co-benefits are an interconnected complex system, it is important to create tools that can offer accurate information and predictions of the co-benefits. These tools also offer more chances to identify places for alternative funding for GSI beyond water related organizations. This study compares and evaluates the differences between three tools, the Green Values National Stormwater Management Calculator, the Environmental Protection Agency’s National Stormwater Calculator, and the Community-enabled Lifecycle Analysis of Stormwater Infrastructure Costs tool. Each tool offers a detailed analysis of different parts of the GSI selection, from life-cycle cost analysis to the variety of co-benefits offered to the level of performance of the BMP in stormwater management. This study is conducted by evaluating five representative rain gardens for the city of Philadelphia, and simulating their effects through each tool to examine data requirements and outputs. The results indicate functionality, ease of use, similarity and/or dissimilarity of the estimated hydrologic results, water quality, cost, and co-benefits of these tools. Co-benefit considerations may inform possibilities for leveraging funding from multiple utilities in a city. The Green Values Tool is the easiest to use, with the EPA Stormwater Calculator and the CLASIC Tool requiring more detailed inputs and handlings. The CLASIC Tool offers both the most detailed and highest number of co-benefits, the Green Values Tool offers some co-benefit analysis, and the EPA Stormwater Calculator did not cover co-benefits at all. All three tools contain a cost analysis function where the analysis for the CLASIC Tool and the Green Values Tool are similar, but the EPA Stormwater Calculator differs. The CLASIC Tool and the EPA Stormwater Calculator provide alike hydrologic budgets but the Green Values Tool estimates tends to vary. The CLASIC Tool is the only tool that provides water quality estimates. By analyzing and comparing the three tools, better choices can be made by governments and communities and offer more opportunities to look for alternative funding for GSI projects, all of which offer a healthier and greener future to the world

Towards Understanding closed-loop PLM: The Role of Product Usage Data for Product Development enabled by intelligent Properties

Product lifecycle management (PLM) is a strategy of managing a company’s products all the way across their lifecycles. Empowered by new capabilities, intelligent products enable seamless information flow and thus enable closed-loop PLM. Hence, one phenomenon of particular interest is the appreciation of beginning of life activities through middle of life information. Grounded on empirical data from a multiple-case study in three distinct manufacturing industries, we explore this emergent role of product usage data for product development. In detail, we address rationales, opportunities, conditions, and obstacles. Findings indicate that (1) heterogeneous motives drive the exploitation, (2) a positive impact on every product development stage is perceivable, (3) some products and industry ecosystems are more suitable than others, and (4) technical, economic, and social obstacles challenge the exploitation. With the limitation of an interpretive, qualitative research design, our work represents a first step to understand the role of closed-loop PLM

The Knowledge Application and Utilization Framework Applied to Defense COTS: A Research Synthesis for Outsourced Innovation

Purpose -- Militaries of developing nations face increasing budget pressures, high operations tempo, a blitzing pace of technology, and adversaries that often meet or beat government capabilities using commercial off-the-shelf (COTS) technologies. The adoption of COTS products into defense acquisitions has been offered to help meet these challenges by essentially outsourcing new product development and innovation. This research summarizes extant research to develop a framework for managing the innovative and knowledge flows. Design/Methodology/Approach – A literature review of 62 sources was conducted with the objectives of identifying antecedents (barriers and facilitators) and consequences of COTS adoption. Findings – The DoD COTS literature predominantly consists of industry case studies, and there’s a strong need for further academically rigorous study. Extant rigorous research implicates the importance of the role of knowledge management to government innovative thinking that relies heavily on commercial suppliers. Research Limitations/Implications – Extant academically rigorous studies tend to depend on measures derived from work in information systems research, relying on user satisfaction as the outcome. Our findings indicate that user satisfaction has no relationship to COTS success; technically complex governmental purchases may be too distant from users or may have socio-economic goals that supersede user satisfaction. The knowledge acquisition and utilization framework worked well to explain the innovative process in COTS. Practical Implications – Where past research in the commercial context found technological knowledge to outweigh market knowledge in terms of importance, our research found the opposite. Managers either in government or marketing to government should be aware of the importance of market knowledge for defense COTS innovation, especially for commercial companies that work as system integrators. Originality/Value – From the literature emerged a framework of COTS product usage and a scale to measure COTS product appropriateness that should help to guide COTS product adoption decisions and to help manage COTS product implementations ex post

Benchmarking performance management systems

The Balanced Scorecard and associated performance management approaches, has become a widely practiced and popular management reporting method in recent times. Moreover, enabling technology, which assists in the delivery and personalisation of corporate performance information, is having a deeper and more rapid impact than ever before. This paper presents a brief comparative benchmarking study of leading enterprise performance management systems. Also, the author discusses the merits of bespoke internet technology development and out-of-the-box portal functionalities. An analysis of key business drivers and implementation risks of such approaches is highlighted via a case study example, and concludes the paper

The Challenges in SDN/ML Based Network Security : A Survey

Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056