The urban energy transition is crucial for a sustainable future. To support this transition, Digital Twins are employed in an increasing fashion, providing decision makers with data-driven insights from mainly technological perspectives. Based on a case study of a neighbourhood in a Dutch municipality, we argue the need to address social perspectives more explicitly while employing Digital Twins. To this end, we identify three potential strategies for an integrated socio-technological approach for Digital Twins. These strategies are modelling social characteristics at a macro-economic scale, involving stakeholders in participatory approaches, and finally explicitly modelling stakeholder behaviour. Given its promise for our case study, we elaborate this last strategy with a conceptual method that aims to explicitly model citizens’ decision-making processes through an agent-based modelling approach.
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This conference explored the collaboration between the Netherlands and Flanders in the field of smart cities. It delved into shared challenges, innovative solutions, and opportunities for cross-border cooperation. Practical workshops covered topics such as applying the latest technologies and using digital twins for smart city development. The event also showcased inspiring projects in areas like sustainable mobility and drone-based security. Networking opportunities were available for professionals and experts to connect and share experiences. The collaboration extended beyond borders, leveraging the similarities and differences in approaches to find solutions. Breda, located on the border of the Netherlands and Flanders, facilitated knowledge exchange and collaboration. The event provided a valuable opportunity for learning and collaboration between the two regions.
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Expectations are high for digital technologies to address sustainability related challenges. While research into such applications and the twin transformation is growing rapidly, insights in the actual daily practices of digital sustainability within organizations is lacking. This is problematic as the contributions of digital tools to sustainability goals gain shape in organizational practices. To bridge this gap, we develop a theoretical perspective on digital sustainability practices based on practice theory, with an emphasis on the concept of sociomateriality. We argue that connecting meanings related to sustainability with digital technologies is essential to establish beneficial practices. Next, we contend that the meaning of sustainability is contextspecific, which calls for a local meaning making process. Based on our theoretical exploration we develop an empirical research agenda.
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Steeds vaker worden digital twins gebruikt om de publieke ruimte anders te organiseren. Dat heeft invloed op het welzijn van burgers. Maar de meeste burgers hebben weinig kennis over die technologie, zien Anne-Marie Sweep, Brishna Nader en Bart Wernaart. Hoe bevraag je hen dan toch over wat ze wel of niet met digitaltwin-technologie willen?
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Hoe kan Digital Twin-technologie de Nederlandse maakindustrie helpen om efficiënt energiezuinig en circulair te werken? Met praktijkgericht onderzoek helpt het lectoraat Industriële Digital Twins van de Hogeschool van Amsterdam (HvA) bedrijven om CO2-neutraal te worden en daarmee internaal competitief te blijven.
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Within the context of the Iliad project, the authors present early design mock-ups and resulting technical challenges for a 2D/3D/4D geo-data visualisation application focused on microparticle flows. The Iliad – Digital Twins of the Ocean project (EU Horizon 2020) aims to develop a ‘system of systems’ for creating cutting-edge digital twins of specific sea and ocean areas for diverse purposes related to their sustainable use and protection. One of the Iliad pilots addresses the topic of water quality monitoring by creating an application offering dynamic 2D and 3D visualisations of specifically identified microparticles, initially observed by buoys/sensors deployed at specific locations and whose subsequent flows are modelled by separate software. The main upcoming technical challenges concern the data-driven approach, where the application’s input data is completely obtained through external API-based services offering (near) real-time observed data from buoys/sensors and simulated data emanating from particle transport models
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Human Digital Twins are an emerging type of Digital Twin used in healthcare to provide personalized support. Following this trend, we intend to elevate our virtual fitness coach, a coaching platform using wearable data on physical activity, to the level of a personalized Human Digital Twin. Preliminary investigations revealed a significant difference in performance, as measured by prediction accuracy and F1-score, between the optimal choice of machine learning algorithms for generalized and personalized processing of the available data. Based on these findings, this survey aims to establish the state of the art in the selection and application of machine learning algorithms in Human Digital Twin applications in healthcare. The survey reveals that, unlike general machine learning applications, there is a limited body of literature on optimization and the application of meta-learning in personalized Human Digital Twin solutions. As a conclusion, we provide direction for further research, formulated in the following research question: how can the optimization of human data feature engineering and personalized model selection be achieved in Human Digital Twins and can techniques such as meta-learning be of use in this context?
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