Integrating artificial intelligence (AI) with immersive analytics (IA) represents a promising means of leveraging advanced computational techniques to enhance data visualization and analysis. This study examines the state-of-the-art of AI-IA integration by addressing three key research issues: the significant application domains, the AI techniques used and their combinations, and current challenges and future directions. Results of reviewing 43 relevant studies reveal that AI-IA integration is still in its early stages, as existing research has mainly focused on a limited range of data types and application scenarios. By analyzing the application domains, this systematic literature review supports previous findings of important applications in the fields of education, manufacturing, and healthcare. At the same time, it identifies emerging applications that have progressed from XR and AI domains to AI-IA integration, such as sports events, assistive systems, urban planning, and disaster management. We contribute to extending established visual analytics (VA) pipelines into XR environments with integrated AI techniques. AI techniques are identified as contributing in five ways to this IA pipeline. Our contribution also includes identifying four key challenges and seven opportunities for future exploration. The review concludes that combining AI and IA holds the potential to create innovative applications using advanced AI and immersive visualization techniques. We present an overview of these applications and address key issues for future development. 

In the District Heating (DH) sector, the analysis and monitoring of data from DH substations is crucial to keeping the entire DH network running efficiently. Clustering of DH substations based on multivariate data helps analyze their behavior over time. In this context, a visualization-based analysis approach can be particularly beneficial. In this paper, we explore the use of dynamic hypergraph visualization to analyze the clustering results of DH network substations over time. We present the initial results of designing and implementing a visual analytics dashboard that supports DH experts in analyzing different behaviors of DH substations. In the proposed dashboard, we adopt the Parallel Aggregated Ordered Hypergraph (PAOH) technique to visualize dynamic hypergraphs, which provides a compact visualization of multivariate data clustering over time. Moreover, we include additional views with complementary visualizations supporting the analysis and understanding of the dynamic hypergraph main view. We showcase the capability of our dashboard applied on a real DH dataset.

Generative artificial intelligence (GenAI) models have advanced various applications with their ability to generate diverse forms of information, including text, images, audio, video, and 3D models. In visual computing, their primary applications have focused on creating graphic content and enabling data visualization on traditional desktop interfaces, which help automate visual analytics (VA) processes. With the rise of affordable immersive technologies, such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), immersive analytics (IA) has been an emerging field offering unique opportunities for deeper engagement and understanding of complex data in immersive environments (IEs). However, IA system development remains resource-intensive and requires significant expertise, while integrating GenAI capabilities into IA is still under early exploration. Therefore, based on an analysis of recent publications in these fields, this position paper investigates how GenAI can support future IA systems for more effective data exploration with immersive experiences. Specifically, we discuss potential directions and key issues concerning future GenAI-supported IA applications. 

Electrodermal activity is considered one of the more reliable methodologies to assess emotional arousal, and it has been adopted as an alternative method for the analysis of player experience in video game research. In this study, we present a quantitative evaluation of self-contained electrodermal measurements, focusing on the analysis of the tonic component and its potential relationship with player experience. The analysis presents a frequency-domain feature quantification of the tonic component, named gradual changes. With it, we evaluate how the variation of the tonic component correlates with the player experience valence, in a set virtual reality games. The analysis also offers an evaluation of the prediction capabilities of the gradual changes, to classify player experience, using a supervised learning approach. Our results support the idea that the tonic component correlates with player experience, statistically demonstrating that a higher number of gradual changes feature a directly proportional relationship with a negative valence in player experience. Despite this, the gradual changes featured a rather limited prediction capability upon player experience, motivating future work in this area.

In this presentation, I will summarize the work done to prepare and run a course module regarding Gender and Social Equality (Jämställdhet och Jämlikhet) offered to first-year students of a Bachelor of Engineering program (Högskoleingenjör i teknisk spelgrafik). The module has been developed as part of an introductory course (Game Development in Technical Game-graphics). The goal of this module is for the students to acquire basic knowledge on the topic and start relevant discussions about gender and social equality in relation to the industry the students are targeting with their study, in this case, the gaming industry and the world of digital games.

During the last decade, we have witnessed a rapiddevelopment of extended reality (XR) technologies such asaugmented reality (AR) and virtual reality (VR). Further, therehave been tremendous advancements in artificial intelligence(AI) and machine learning (ML). These two trends will havea significant impact on future digital societies. The vision ofan immersive, ubiquitous, and intelligent virtual space opensup new opportunities for creating an enhanced digital world inwhich the users are at the center of the development process,so-calledintelligent realities(IRs).The “Human-Centered Intelligent Realities” (HINTS) profileproject will develop concepts, principles, methods, algorithms,and tools for human-centered IRs, thus leading the wayfor future immersive, user-aware, and intelligent interactivedigital environments. The HINTS project is centered aroundan ecosystem combining XR and communication paradigms toform novel intelligent digital systems.HINTS will provide users with new ways to understand,collaborate with, and control digital systems. These novelways will be based on visual and data-driven platforms whichenable tangible, immersive cognitive interactions within realand virtual realities. Thus, exploiting digital systems in a moreefficient, effective, engaging, and resource-aware condition.Moreover, the systems will be equipped with cognitive featuresbased on AI and ML, which allow users to engage with digitalrealities and data in novel forms. This paper describes theHINTS profile project and its initial results. ©2023, Copyright held by the authors   

Thanks to its effectiveness, electrodermal activity (EDA) has been previously included as an evaluation metric, within analyses of user experience. In this study, the phasic component of participants’ EDA data is examined in relation to their reported experiences when playing a set of virtual reality games, that featured the HTC Vive and Leap Motion controllers for input. Two models are used in the analysis of the phasic component: a deconvolution model and a convex optimization model. Despite having significant differences in their player experiences, results indicate that there are not many significant differences in the phasic component data. Even if some weak correlations were found, the majority of results show no linear correlations between the phasic component data and the reported experience variables. This shows that the phasic component of EDA data should be further investigated in conjunction with other psychophysiological signals because it has only recently demonstrated a weak link with player experience. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

This systematic literature review presents an update on developments in 3D visualization techniques and analysis tools for eye movement data in 3D environments. With the introduction of affordable and non-intrusive eye-tracking solutions to the mass market, access to users' gaze is now increasingly possible. As a result, the adoption of eye-tracking in virtual environments using head-mounted displays is expected to increase since the trend is to incorporate gaze tracking as part of new technical solutions. The systematic literature review presented in this paper was conducted using the Scopus database (using the period 2017 to 17th of May 2022), which after analysis, resulted in the inclusion of 15 recent publications with relevance in eye-tracking visualization techniques for 3D virtual scenes. First, this paper briefly describes the foundations of eye-tracking and traditional 2D visualization techniques. As background, we also list earlier 3D eye-tracking visualization techniques identified in a previous review. Next, the systematic literature review presents the method used to acquire the included papers and a description of these in terms of eye-tracking technology, observed stimuli, application context, and type of 3D gaze visualization techniques. We then discuss the overall findings, including opportunities, challenges, trends, and present ideas for future directions. Overall the results show that eye-tracking in immersive virtual environments is on the rise and that more research and developments are needed to create novel and improved technical solutions for 3D gaze analysis.

Augmented Reality (AR) and 3D printing have increasingly been used in archaeological and cultural heritage to make artifacts and environments accessible to the general public. This paper presents the case study of the Ljungaviken dog, an archaeological find of dog skeleton remains dated around 8000 years ago. The dog remains have been digitized using 3D scanning and displayed in an AR application. A physical replica has also been created with 3D printing. Both the AR application and the 3D printed copy have been shown in a temporary museum exhibition. In this paper, we present the visitors’ experience evaluation based on a study with 42 participants. Aspects being evaluated are related to the realism, enjoyment, and easiness of use of the AR application. Moreover, the two media are compared in terms of understanding, visual quality, and experience satisfaction. The results show an overall positive experience for both the display solutions, with slightly higher scores for the AR application in the comparison. When asked about overall preference, the participants reported similar results between both media. Due to issues of displaying fragile objects in a museum setting, as well as recent restrictions following pandemic closures and availability, the results presented in this paper show a positive alternative towards using digital artifacts to showcase our cultural heritage. © 2022, Springer Nature Switzerland AG.

Electrodermal activity (EDA) is considered to be an effective metric for measuring changes in the arousal level of people. In this paper, the phasic component of EDA data from players is analyzed in relation to their reported experience from a standardized questionnaire, when interacting with a couple of virtual reality games that featured two different input devices: the HTC Vive and Leap Motion controllers. Initial results show that there are no significant differences in the phasic component data, despite having significant differences in their respective player experience. Furthermore, no linear correlations are found between the phasic component data and the evaluated experience variables, with the only exception of negative affect which features a weak positive correlation. In conclusion, the phasic component of EDA data has here shown a limited correlation with player experience and should be further explored in combination with other psychophysiological signals.