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Smart electric vehicles (SEVs) hold significant potential in alleviating the energy crisis and environmental pollution. The augmented reality (AR) dashboard, a key feature of SEVs, is attracting considerable attention due to its ability to enhance driving safety and user experience through real-time, intuitive driving information. This study innovatively integrates Kansei engineering, factor analysis, fuzzy systems theory, analytic hierarchy process, grey relational analysis, and factorial experimentation to evaluate AR dashboards’ visual imagery and subjective preferences. The findings reveal that designs featuring blue planar and unconventional-shaped dials exhibit the best performance in terms of visual imagery. Subsequent factorial experiments confirmed these results, showing that drivers most favor blue-dominant designs. Furthermore, in unconventional-shaped dial designs, the visual effect of vertical 3D is more popular with drivers than horizontal 3D, while the opposite is true in round dials. This study provides a scientific evaluation method for assessing the emotional experience of AR dashboard interfaces. Additionally, these findings will help reduce the subjectivity in interface design and enhance the overall competitiveness of SEV vehicles.

This research study investigates the impact of a virtual dashboard on the quality of task execution in robotic teleoperation. More specifically, this study investigates how a virtual dashboard improves user awareness and grasp precision in a teleoperated pick-and-place task by providing users with critical information in real-time. An experiment was conducted with 30 participants in a robotic teleoperated task to measure their task performance in two different experimental conditions: a control group used conventional interfaces, and an experimental group utilized the virtual dashboard with additional information. Research findings indicate that integrating a virtual dashboard improves grasping accuracy, reduces user fatigue, and speeds up task completion, thereby improving task effectiveness and the quality of the experience.

The development of information and communication technologies has created limitless prospects for using augmented reality (AR) in various fields. Unfortunately, the multitasking nature of AR systems prevents learners from successfully reflecting and retaining knowledge. This study developed and designed a learning analytics dashboard (LAD) with three components: personal learning data, social comparison, and visualization of the learning process, to promote knowledge acquisition and metacognitive awareness among AR learners. A total of 31 intermediate-level Japanese learners participated in an experiment involving pre-tests, post-tests, and a delayed test to assess the LAD. Learners engaged with the AR learning system for Japanese compound verb learning and utilized the LAD to monitor and reflect on their AR learning activities. Behavioral data were analyzed using Lag Sequential Analysis (LSA), while learning performance was evaluated through one-way repeated-measures ANOVA tests. The findings indicate that the use of the LAD significantly improves learning outcomes and metacognitive processes, such as knowledge of cognition and regulation of cognition. Additionally, there were different usage patterns of the dashboard among learners, which corresponded to significant differences in their learning outcomes and changes in metacognitive awareness. Learners who primarily focused on the learning process and social comparison components of the dashboard demonstrated improved knowledge retention. Conversely, those who mainly concentrated on personal learning data experienced the most significant gains in metacognitive awareness. This study also provides crucial design insights on the integration of dashboard components with cognitive efforts to maximize learning outcomes. Plain language summary Improving Language Learning Through a Dashboard: A Study on Japanese Learners Using Augmented Reality This study examined the effectiveness of a learning analytics dashboard (LAD) with three components (personal learning data, social comparison, and visualization of the learning process) in promoting the knowledge acquisition and metacognitive awareness of 31 non-native learners of Japanese in learning Japanese compound verbs. The results indicated that the use of LAD significantly improves learning outcomes and metacognitive processes, such as knowledge of cognition and regulation of cognition, and second, that students who concentrated on the learning process and social comparison showed the most improved performance in knowledge retention, while those who concentrated on personal learning data showed greater improvements in metacognitive awareness. This study contributes significantly to the field of LA by providing evidence that the integration of LAD into AR learning environments can meet the multifaceted challenges posed by concurrent multitasking, thus facilitating a more monitored and reflective learning experience. The research also highlights the benefits of combining dashboard components with cognitive efforts to ensure that metacognitive awareness is effectively harnessed to improve learning.

The digitisation of urban cultural heritage (CH) is recognised within EU (European Union) policies as an opportunity to make CH a driver for urban transformation towards a sustainable and inclusive future. Various digital platforms are emerging as tools not only to store, retrieve, compare and process different kind of data related to CH for the use of urban planners and administrators, but also as participative tools for distributed decision-making. The increasing integration between the physical and digital realm through various digital instruments such as the Internet of things, virtual and augmented reality, machine learning and natural language processing, has led designers to conceptualise the necessity of merging different smart city dashboards and platforms into an integrated system known as the urban digital twin (DW). This task can be made possible only through the construction of a shared ontology of the city, which allows the interoperability of different data systems. The DWs, originally developed in mechanical and process engineering, allow to construct a digital model of a physical object or process, to monitor its real-time performance, to perform maintenance tasks and to test the effects of planned changes. However, when extending the notion of the DW to complex cultural and social entities such as cities, it is important to consider also issues of inclusivity and citizen participation. How can the DW be conceptualised not only as a tool of technological control or narrative, but as an instrument to empower not only institutions but also citizens? The experience gath- ered in the construction of the ROCK platform and its participatory ontology, developed within the Horizon 2020 (H2020) funded project ROCK (GA 730280), becomes an important precedent in this task

Current regulations to reduce energy consumption, and GHG emissions from buildings have focused on reducing operational impacts [1] This paper addresses the specific challenge of increasing complexity and decreasing usability when dealing with the level of detail required when modelling life cycle assessment (LCA) and integrating embodied emission calculations in the design process of a ZEB. It is well known that architectural design processes inherently have high degrees of complexity, and this paper investigates how the use of information and communication technology (ICT) in the design process can have a great impact on reducing GHG emissions and increasing sustainability in ZEBs. Visualisation is an invaluable tool to communicate complex data in an interactive way that makes it easier for non-expert users to integrate LCA thinking early and throughout the design process. The paper presents a chronology in the development of a more visual, integrated and dynamic approach involving the use of parametric LCA models for decision-support purposes. Such an approach provides the designer with a direct link between the 3D digital model and embodied emissions data contained in the ZEB Tool to perform life cycle GHG emission calculations of buildings. Integrating LCA in a more visual and easily understood way in the holistic design process can also influence more tangible material choices in terms of, for example, architectural tectonics or cultural heritage. This allows designers the possibility to choose, for example, durable or natural materials with the lowest environmental impact or innovative materials with high or low associated emissions and consider these holistically early in the design phase when the level of design freedom is greater. The extent to which existing ICT tools and User Interfaces (UI), such as dashboards, can provide dynamic visual feedback on selected parameters, including LCA, in the design process of zero emission buildings, is discussed. The paper presents two 'proof of concept' dashboards to visualise LCAs at the building (ZEB) and neighbourhood (ZEN) scale. Both approaches are currently being further developed in The ZEN research centre to visualise, analyse and model the data at different scales for different ZEN Key Performance Indicators (KPIs) using visualisation and immersive technologies, such as Extended Reality (XR) technologies including Virtual Reality (VR) and Augmented Reality (AR).

The objective of the work is to describe the design and the realization of a virtual simulator of a metropolitan railway cockpit, aimed at improving the perception of safety by means of tests made by users in Virtual Reality, analysed through statistical methodologies. The user lives the experience of a driver in an immersive and interactive Augmented Reality session, interacting with the train dashboard and all its control and signalling devices. In particular, the user is proposed to test different dashboards, different configurations of the controls and different signalling and safety devices in order to compare different concept and select the optimum in terms of perception of dangerous situation, reaction to an event and cognitive response in different situations of the rail vehicle driving. The simulator consists of a simulacrum integrating different technologies, physically composed of a dashboard of the cockpit of a metropolitan train and a real seat. The geometry of the dashboard has been acquired through Reverse Engineering techniques from a real train dashboard. The user’s immersion in the virtual environment during the simulation is guaranteed by the scene displayed on the Augmented Reality device, while, simultaneously, the stereoscopic projection on a screen above the dashboard makes available the experience even to users not directly involved, seeing the scene from the driver’s point of view. The immersive Augmented Reality is realized through a Head-Mounted Display (HMD) by which the user, protagonist of the driving experience, sees the configuration of the virtual control devices (CAD geometries) overlapped with the physical dashboard in order to naturally interact into the immersive environment. The interaction between user and simulator happens through the NUI (Natural User Interfaces) based on markerless tracking of parts of the user’s body.

This paper looks at different technologies that are being used currently in agricultural education at the University of Queensland (UQ), Australia through the lens of ‘disruption’ as a positive force. The paper describes tools and systems that have been developed, tested and implemented to engage students and provide an interesting, educative interactive experience. These tools include Internet of Things (IoT) multisensory mesh networks and associated data dashboard developments for biophysical monitoring, drone technology design and build for agricultural management, and augmented reality simulations as blended learning experiences. These tools have all been used in teaching from 2018-2020.

Situated Visualization is an emerging field that unites several areas - visualization, augmented reality, human-computer interaction, and internet-of-things, to support human data activities within the ubiquitous world. Likewise, dashboards are broadly used to simplify complex data through multiple views. However, dashboards are only adapted for desktop settings, and requires visual strategies to support situatedness. We propose the concept of AR-based situated dashboards and present design considerations and challenges developed over interviews with experts. These challenges aim to propose directions and opportunities for facilitating the effective designing and authoring of situated dashboards.

Digital Twin (DT) has been widely adopted in construction and infrastructure projects to focus on the management and control of physical systems and assets responsively to meet the users' requirements. When integrating immersion functions with the digital and wireless transformation models, the DT applications can further allow users to interact with and experience the model information in a more engaging and intuitive way. To add new perspectives to DT applications, this research gave reality functions to develop an immersive DT framework and presented a case study of VR- and AR-based bridge health monitoring and twining systems to demonstrate the functionalities. The case study was focused on the Structural Health Monitoring (SHM) processes for a newly constructed extradosed bridge, facilitated by the integration of Building Information Modeling (BIM), Virtual Reality (VR), Augmented Reality, 3D game engines, and Internet of Things (loT) technologies. The bridge's geometric and property information was modeled in BIM parametric design software as a basis for VR model development and was used to develop the BIM-based sensory model in the 3D game engine according to the on-site conditions of the physically installed system. The integrated virtual model was further deployed to the AR device via a VR-to-AR workflow and was presented through the immersive DT dashboard. Project stakeholders can perform bridge damage detection using the information available from the dashboard. In this dashboard the loT tools were used for the multi-source data integration process by storing, processing, and transforming the monitoring data, lending opportunities for predictive simulations of bridge condition states.

Automation Replaces Tasks, Not Work This emergence of a task ecosystem where workers and machines work synchronously is replacing dated automation utopian mindsets like lights-out systems, where even technology pioneers like Elon Musk are citing the importance of human workers and the pitfalls of excessive automation and its detrimental impact on Tesla production. Instead of traditional reprogramming robot procedures, where an operator will have to leave the area to update the robot’s configurations and procedures, AR brings a virtual interactive dashboard to the shop floor in a timely and immersive experience, potentially saving thousands in changeover costs. While guide and visualize capabilities are driving growing adoption of use cases across design, operations, sales & marketing, service, and training, a future frontier for AR innovation will be its untapped potential as an HMI, bridging the work collaboration gap between humans and machines.