Search Results (22)

The AEC’s resource consumption and environmental impact necessitate a shift towards sustainable, circular practices. Building information modeling, powered by information technology, serves as a key enabler in this transition, offering life cycle data management capabilities from design to deconstruction. However, current BIM models lack embedded life cycle and circularity data, limiting their effectiveness for sustainability integration. This study addresses this gap by proposing a BIM object library framework that embeds life cycle, cost, and circularity data into objects and aims at enabling informed, sustainability-driven decision making. Through a proof of concept, this research demonstrates how embedding LCA and CE metrics into BIM objects enhances environmental and circular impact assessments. The framework aligns with standards such as ISO 14040 and EN 15804, EU Level(s), and United Nations’ 2030 Agenda for Sustainable Development. Limitations such as manual data integration and the need for specialized expertise occurred. However, this framework provides a scalable foundation for future research, including automating data integration, enhancing metric calculations, and developing interactive circularity dashboards to improve as a decision-support tool. This study advances circular BIM adoption, integrating sustainability principles into digital design workflows from the object level, while serving as a centralized repository for sustainability-driven decision making. Full article

This research develops and applies a tool that allows the breakdown of time objectives to the same level of detail traditionally applied to cost, while also providing a favorable production scheme to ensure the project quality. This tool introduces an innovative approach to planning and execution monitoring through cascading dashboards, representing production packages and activities across designated project zones. This approach reinterprets the Last Planner System for jobs on-site in conjunction with the Location-Based Management System. The primary dashboard facilitates the management of complex work structures—typically involving hundreds of rows in Gantt chart representations or numerous lines in Line of Balance diagrams—while enabling the easy identification of activity cycles and gaps between activities in each zone. The tool offers a four-dimensional planning visualization—what, where, when, and who—enhancing the understanding of activity sequences and workflows across project zones, while also contributing to product quality improvement. Furthermore, it has been demonstrated through its application that the tool provides reliable, real-time information that supports decision-making, optimizes resource allocation, and improves overall project competitiveness. Full article

This study investigates the integration of Building Information Models (BIMs) and Virtual Tour (VT) environments in the Architecture, Engineering and Construction (AEC) industry, focusing on Computer-Aided Facility Management (CAFM), Computerized Maintenance Management Systems (CMMSs), and data Life-Cycle Assessment (LCA). The interconnected nature of tasks throughout a building’s life cycle increasingly demands a seamless integration of real-time monitoring, 3D models, and building data technologies. While there are numerous examples of effective links between IoT and BIMs, as well as IoT and VTs, a research gap exists concerning VT-BIM integration. This article presents a technical solution that connects BIMs and IoT data using VTs to enhance workflow efficiency and information transfer. The VT is developed upon a pilot based on the Controlled Environments for Living Lab Studies (CELLS), a unique facility designed for flexible monitoring and remote-control processes that incorporate BIMs and IoT technologies. The findings offer valuable insights into the potential of VTs to complement and connect to BIMs from a life-cycle perspective, improving the usability of digital twins for beginner users and contributing to the advancement of the AEC and CAFM industries. Our technical solution helps complete the connectivity of BIMs-VT-IoT, providing an intuitive interface (VT) for rapid data visualisation and access to dashboards, models and building databases. The practical field of application is facility management, enhancing monitoring and asset management tasks. This includes (a) sensor data monitoring, (b) remote control of connected equipment, and (c) centralised access to asset-space information bridging BIM and visual (photographic/video) data. Full article

The benefits of teacher-facing dashboards are incontestable, yet their evidence is finite in terms of long-term use, meaningful usability, and maturity level. Thus, this paper uses design science research and critical theory to design and develop TEADASH to support teachers in making decisions on teaching and learning. Three cycles of design science research and multiple small loops were implemented to develop the dashboard. The tool was then deployed and evaluated in real time with the authentic courses. Five courses from two Swedish universities were included in this study. The co-design with teachers is crucial to the applicability of this dashboard, while letting teachers use the tool during their courses is more important to help them to recognize the features they actually use and the tool’s usefulness for their teaching practices. TEADASH can address the prior matters, align with the learning design, and meet teachers’ needs. The technical and co-design aspects, as well as the advantages and challenges of applying TEADASH in practice, are also discussed here. Full article

As the global population rises, there is an ever-increasing demand for food, in terms of volume, quality and sustainable production. Protected Cropping Structures (PCS) provide controlled farming environments that support the optimum use of crop inputs for plant growth, faster production cycles, multiple growing seasons per annum and increased yield, while offering greater control of pests, disease and adverse weather. Globally, there has been a rapid increase in the adoption of PCS. However, there remains a concerning knowledge gap in the availability of accurate and up-to-date spatial information that defines the extent (location and area) of PCS. This data is fundamental for providing metrics that inform decision making around forward selling, labour, processing and infrastructure requirements, traceability, biosecurity and natural disaster preparedness and response. This project addresses this need, by developing a national map of PCS for Australia using remotely sensed imagery and deep learning analytics, ancillary data, field validation and industry engagement. The resulting map presents the location and extent of all commercial glasshouses, polyhouses, polytunnels, shadehouses and permanent nets with an area of >0.2 ha. The outcomes of the project revealed deep learning techniques can accurately map PCS with models achieving F-Scores > 0.9 and accelerate the mapping where suitable imagery is available. Location-based tools supported by web mapping applications were critical for the validation of PCS locations and for building industry awareness and engagement. The final national PCS map is publicly available through an online dashboard which summarises the area of PCS structures at a range of scales including state/territory, local government area and individual structure. The outcomes of this project have set a global standard on how this level of mapping can be achieved through a collaborative, multifaceted approach. Full article

Learning Analytics Dashboards (LADs) can help provide insights and inform pedagogical decisions by supporting the analysis of large amounts of educational data, obtained from sources such as Digital Learning Materials (DLMs). Extracting requirements is a crucial step in developing a LAD, as it helps identify the underlying design problem that needs to be addressed. In fact, determining the problem that requires a solution is one of the primary objectives of requirements extraction. Although there have been studies on the development of LADs for K12 education, these studies have not specifically emphasized the use of a Human-Centered Design (HCD) approach to better comprehend the teachers’ requirements and produce more stimulating insights. In this paper we apply prototyping, which is widely acknowledged as a successful way for rapidly implementing cost-effective designs and efficiently gathering stakeholder feedback, to elicit such requirements. We present a three-step HCD approach, involving a design cycle that employs paper and interactive prototypes to guide the systematic and effective design of LADs that truly meet teacher requirements in primary/secondary education, actively engaging them in the design process. We then conducted interviews and usability testing to co-design and develop a LAD that can be used in classroom’s everyday learning activities. Our results show that the visualizations of the interactive prototype were easily interpreted by the participants, verifying our initial goal of co-developing an easy-to-use LAD. Full article

This paper conceptualizes the use of interactive urban dashboards in collecting and visualizing sustainability indicators at local scales through a cycling dashboard prototype for Münster. Urban dashboards are integrated platforms that bring various data types and sources together and automatize the visualization of information in real time. They can function as information hubs that work with mobile applications, sensor-based data, and crowdsourced platforms. Visualization of information can present both map-based data, text, and graphical information. In this study, a cycling dashboard is introduced that is developed as a prototype. The dashboard is based on the sustainability indicators related to cycling infrastructure defined by the German Sustainable Building Council (DGNB). It retrieves crowdsourced open data from Open Street Map (OSM) and automatically updates the information when new data are entered into the platform. This enables detailed exploration of the geo-referenced information up to street level and comparisons between different districts. In order to achieve a comprehensive framework, four main steps were included into the design and development process “determining a content by integrating future users, creating and evaluating a data inventory, designing the architecture of the dashboard, and implementing the prototype ”. As a result, this study holistically draws a comprehensive framework for the urban cycling dashboard around three main modules focusing on the sustainability of cycling infrastructure “infrastructure guide, cyclists’ voice, and idea center”. Additionally, the first prototype of an open local cycling dashboard has been implemented. The prototype enables the automation of collection, analysis, visualisation, and deep exploration of sustainability-related data at local scales. The results of this study contribute to the status quo by supporting the design and development process of local urban dashboards through a participatory approach. Full article

The aim of this study is the evaluation of Life Cycle Sustainability Assessment (LCSA) visualizations, which have been gaining increasing relevance in recent years. Despite this, the final interpretation and visualization of LCSA are not yet sufficiently established. Three of the existing LCSA visualization tools, Life Cycle Sustainability Triangle (LCST), Life Cycle Sustainability Dashboard (LCSD), and Sustainability Crowns, are compared and discussed along previously established target criteria. Subsequently, a “new” visualization tool (LCSA-Wheel) is developed based on analysis results and tested within a case study. It became clear that the LCST and Sustainability Crowns are mainly used to help weigh the sustainability dimensions. Nevertheless, the Sustainability Crowns meet most of the defined target criteria and thus serve as a model for the development of a visualization approach. The LCSD maps a wealth of information but is more difficult to understand without a deeper dive into the topic. The proposed LCSA-Wheel adopts a clear structure and provides information needed to understand the visualization. Although further developments are still necessary for general applicability, there is a justified assumption, shown with the help of a case study, that the LCSA-Wheel will gain acceptance in science and practice and thus drive the use of the LCSA. Full article

This paper presents a bibliometric systematic review on model-based learning analytics (MbLA), which enable coupling between teachers and intelligent systems to support the learning process. This is achieved through systems that make their models of student learning and instruction transparent to teachers. We use bibliometric network analysis and topic modelling to explore the synergies between the related research groups and the main research topics considered in the 42 reviewed papers. Network analysis depicts an early stage community, made up of several research groups, mainly from the fields of learning analytics and intelligent tutoring systems, which have had little explicit and implicit collaboration but do share a common core literature. Th resulting topics from the topic modelling can be grouped into the ones related to teacher practices, such as awareness and reflection, learning orchestration, or assessment frameworks, and the ones related to the technology used to open up the models to teachers, such as dashboards or adaptive learning architectures. Moreover, results show that research in MbLA has taken an individualistic approach to student learning and instruction, neglecting social aspects and elements of collaborative learning. To advance research in MbLA, future research should focus on hybrid teacher–AI approaches that foster the partnership between teachers and technology to support the learning process, involve teachers in the development cycle from an early stage, and follow an interdisciplinary approach. Full article

Harvesting is an integral component of the agricultural cycle, necessitating the use of high-performance grain harvester combines, which are utilized for a short period each year. Given the seasonality and significant cost involved, list prices ranging from a quarter to almost a million euros, a fact-based investment assessment decision-making process is essential. However, there is a paucity of research studies forecasting the remaining value of grain harvester combines in recent years. This study proposes a straightforward methodology based on public information that employs various parametric and non-parametric models to develop a robust and user-friendly model that can assist decision makers, such as farmers, contractors, sellers, and finance and insurance entities, in optimizing their harvesting operations. The model employs a power regression mode, with RMSE of 1.574 and RSqAdj of 0.8457 results, to provide accurate and reliable insights for informed decision-making. The robust model transparency enables us to easily create a mainstreamed spreadsheet-based dashboard tool. Full article

Unhealthy diets and excess energy intake are the greatest contributors to disease and disability in Aotearoa. Unhealthy diets are heavily influenced by obesogenic food environments. Governments and the private sector have critical roles to play in creating healthier food environments, yet New Zealand consistently falls behind international best practice, suggesting a lack of accountability. The accountability cycle has five phases: setting the account, taking account, sharing the account, holding to account, and responding to the account. The ongoing monitoring of the healthiness of food environments is essential to identify key problems, assess the impact of policies, hold governments and food companies to their commitments, measure progress, and support future implementation. The Food Environments Dashboard Aotearoa was created to collate and translate more than a decade’s worth of food environment monitoring studies and their findings for policy-makers and public health advocacy groups to encourage policy change. Based on Australia’s Food Environments Dashboard, the key indicators from these studies have been identified and assessed against defined criteria to give a green (promotes health), amber (needs improvement) or red (unhealthy) rating. Data from studies implemented between 2014 and 2022 were reviewed and 65 key indicators were selected for ten domains: government, food composition, settings (schools, hospitals), food labelling, food affordability, food promotion, food retail, private sector, trade and investment, and equity. Most domains were assessed as red and none as green. The Dashboard contributes to sharing and holding to account by providing key indicators in an accessible format that will be regularly updated. We encourage the public health nutrition community of practice to contribute to, and utilise, the Dashboard to improve food environments for Aotearoa. Full article

Natural hazards are increasingly threatening our communities; hence it is imperative to provide communities with reliable information on possible impacts of such disasters, and on resilience measures that can be adopted to recover from disasters. To increase the engagement of various stakeholders in decision-making processes related to resilience to natural hazards, problem-specific information needs to be presented to them in a language understandable to non-experts in the field. To this end, this paper illustrates experimentation with low-code platforms for fast digitalization of resilience reports, incorporating the perspectives of various stakeholders in the analysis, thus making informed decision-making practicable. We present a co-creation-based approach to develop GIS-based user-friendly dashboards in support to the identification of resilience strategies against natural hazards; this approach has been developed within the framework of the European project ARCH. Urban areas are regarded as complex social-ecological systems whose various dimensions should be considered in this resilience endeavor, during all phases of the Disaster Risk Reduction and Climate Change Adaptation cycle. The work presented in this paper specifically targets the possible impacts and risks that might affect the cultural heritage subsystems of our cities, generally underrepresented in the international literature related to urban resilience assessment. We describe how we applied our approach to the Camerino municipality, a historic Italian town exposed to seismic risk, which was struck by a severe earthquake sequence in 2016–2017 and discuss the results of our experience. Full article

The ready-mix concrete supply chain is highly disruptive due to its product perishability and Just-in-Time (JIT) production style. A lack of technology makes the ready-mix concrete (RMC) industry suffer from frequent production failures, ultimately causing high customer dissatisfaction and loss of revenues. In this paper, we propose the first-ever digital twin (DT) system in the RMC industry that can serve as a decision support tool to manage production risk efficiently and effectively via predictive maintenance. This study focuses on the feasibility of digital twins for the RMC industry in three main areas holistically: (1) the technical feasibility of the digital twin system for ready-mix concrete plant production risk management; (2) the business value of the proposed product to the construction industry; (3) the challenges of implementation in the real-world RMC industry. The proposed digital twin system consists of three main phases: (1) an IoT system to get the real-time production cycle times; (2) a digital twin operational working model with descriptive analytics; (3) an advanced analytical dashboard with predictive analytics to make predictive maintenance decisions. Our proposed digital twin solution can provide efficient and interpretable predictive maintenance insights in real time based on anomaly detection, production bottleneck identification, process disruption forecast and cycle time analysis. Finally, this study emphasizes that state-of-the-art solutions such as digital twins can effectively manage the production risks of ready-mix concrete plants by automatically detecting and predicting the bottlenecks without waiting until a production failure happens to react. Full article

Business owners and managers need strategic information to plan and execute their decisions regarding business operations. They work in a cyclic plan of execution and evaluation. In order to run this cycle smoothly, they need a mechanism that should access the entire business performance. The sole purpose of this study is to assist them through applied research framework-based analysis to obtain effective results. The backbone of the purposed framework is a hybrid mechanism that comprises business intelligence (BI) and machine learning (ML) to support 360-degree organization-wide analysis. BI modeling gives descriptive and diagnostic analysis via interactive reports with quick ad hoc analysis which can be performed by executives and managers. ML modeling predicts the performance and highlights the potential customers, products, and time intervals. The whole mechanism is resource-efficient and automated once it binds with the operational data pipeline and presented results in a highly efficient manner. Data analysis is far more efficient when it is applied to the right data at the right time and presents the insights to the right stakeholders in a friendly, usable environment. The results are beneficial to viewing the past, current, and future performance with self-explanatory graphical interpretation. In the proposed system, a clear performance view is possible by utilizing the sales transaction data. By exploring the hidden patterns of sales facts, the impact of the business dimensions is evaluated and presented on a dynamically filtered dashboard. Full article

Life Cycle Assessment (LCA) computes potential environmental impacts of a product or process. However, LCAs in the industrial sector are generally delivered through static yearly analyses which cannot capture any temporal dynamics of inventory data. Moreover, LCA must deal with differences across background models, Life Cycle Impact Assessment (LCIA) methods and specific rules of environmental labels, together with their developments over time and the difficulty of the non-expert organization staff to effectively interpret LCA results. A case study which discusses how to manage these barriers and their relevance is currently lacking. Here, we fill this gap by proposing a general methodology to develop a modular tool which integrates spreadsheets, LCA software, coding and visualization modules that can be independently modified while leaving the architecture unchanged. We test the tool within the ORI Martin secondary steelmaking plant, finding that it can manage (i) a high amount of primary foreground data to build a dynamic LCA; (ii) different background models, LCIA methods and environmental labels rules; (iii) interactive visualizations. Then, we outline the relevance of these capabilities since (i) temporal dynamics of foreground inventory data affect monthly LCA results, which may vary by ±14% around the yearly value; (ii) background datasets, LCIA methods and environmental label rules may alter LCA results by 20%; (iii) more than 10⁵ LCA values can be clearly visualized through dynamically updated dashboards. Our work paves the way towards near-real-time LCA monitoring of single product batches, while contextualizing the company sustainability targets within global environmental trends. Full article