Immersive Analytics as a Support Medium for Data-Driven Monitoring in Hydropower

Information

• Publication Type: Journal Paper (without talk)
• Workgroup(s)/Project(s): not specified
• Date: May 2025
• DOI: 10.1109/TVCG.2025.3549157
• ISSN: 1941-0506
• Journal: IEEE Transactions on Visualization and Computer Graphics
• Number: 5
• Pages: 11
• Volume: 31
• Publisher: IEEE COMPUTER SOC
• Pages: 3536 – 3546
• Keywords: Immersive Analytics, Data Visualization, Digitalization, Egocentric navigation, Spatial Data, User Evaluation

Abstract

Hydropower turbines are large-scale equipment essential to sustainable energy supply chains, and engineers have few opportunities to examine their internal structure. Our Immersive Analytics (IA) application is part of a research project that combines and compares simulated water turbine flows and sensor-measured data, looking for data-driven predictions of the lifetime of the mechanical parts of hydroelectric power plants. Our prototype combines spatial and abstract data in an immersive environment in which the user can navigate through a full-scale model of a water turbine, view simulated water flows of three different energy supply conditions, and visualize and interact with sensor-collected data situated at the reference position of the sensors in the actual turbine. In this paper, we detail our design process, which resulted from consultations with domain experts and a literature review, give an overview of our prototype, and present its evaluation, resulting from semi-structured interviews with experts and qualitative thematic analysis. Our findings confirm the current literature that IA applications add value to the presentation and analysis of situated data, as they show that we advance in the design directions for IA applications for domain experts that combine abstract and spatial data, with conclusions on how to avoid skepticism from such professionals.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1109/TVCG.2025.3549157

BibTeX

@article{medeiros-2025-iaa,
  title =      "Immersive Analytics as a Support Medium for Data-Driven
               Monitoring in Hydropower",
  author =     "Marina Lima Medeiros and Hannes Kaufmann and Johanna Schmidt",
  year =       "2025",
  abstract =   "Hydropower turbines are large-scale equipment essential to
               sustainable energy supply chains, and engineers have few
               opportunities to examine their internal structure. Our
               Immersive Analytics (IA) application is part of a research
               project that combines and compares simulated water turbine
               flows and sensor-measured data, looking for data-driven
               predictions of the lifetime of the mechanical parts of
               hydroelectric power plants. Our prototype combines spatial
               and abstract data in an immersive environment in which the
               user can navigate through a full-scale model of a water
               turbine, view simulated water flows of three different
               energy supply conditions, and visualize and interact with
               sensor-collected data situated at the reference position of
               the sensors in the actual turbine. In this paper, we detail
               our design process, which resulted from consultations with
               domain experts and a literature review, give an overview of
               our prototype, and present its evaluation, resulting from
               semi-structured interviews with experts and qualitative
               thematic analysis. Our findings confirm the current
               literature that IA applications add value to the
               presentation and analysis of situated data, as they show
               that we advance in the design directions for IA applications
               for domain experts that combine abstract and spatial data,
               with conclusions on how to avoid skepticism from such
               professionals.",
  month =      may,
  doi =        "10.1109/TVCG.2025.3549157",
  issn =       "1941-0506",
  journal =    "IEEE Transactions on Visualization and Computer Graphics",
  number =     "5",
  pages =      "11",
  volume =     "31",
  publisher =  "IEEE COMPUTER SOC",
  pages =      "3536--3546",
  keywords =   "Immersive Analytics, Data Visualization, Digitalization,
               Egocentric navigation, Spatial Data, User Evaluation",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2025/medeiros-2025-iaa/",
}