Adaptive Visualization Framework for Human-Centric Data Interaction in Time-Critical Environments

Alexopoulos, Andreas;Vanderdonckt, Jean;Leiva, Luis A.;Arapakis, Ioannis;Prevelakis, Vassilis;et.al.
(2024) 11th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications — Location: Lausanne, Switzerland (25.April.2024)

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Authors
  • Alexopoulos, AndreasAEGIS IT RESEARCH GmbH
    Author
  • Vanderdonckt, Jeanorcid-logoUCLouvain
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  • Leiva, Luis A.orcid-logoUniversity of Luxembourg
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  • Arapakis, Ioannisorcid-logoTelefonica
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  • Prevelakis, Vassilisorcid-logo
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Abstract
In today's data-driven era, handling information overload in time-sensitive scenarios poses a significant challenge. Visualization is a valuable tool for comprehending vast amounts of data. However, it's crucial to have self-adapting visualizations that are tailored to the user's cognitive level and grow with their expertise. Existing solutions often fall short in this regard. This paper introduces a framework integrating Artificial Intelligence (AI) techniques for context awareness and emotion sensing, offering visualizations that adjust to user requirements. The framework makes use of cross-modal sensors and Machine Learning(ML) algorithms to analyse behavioural signals, usage statistics, and user feedback. This data guides real-time data ingestion techniques and ML-driven mechanisms, ensuring that visualizations adapt while safeguarding data privacy and confidentiality
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Alexopoulos, A., Vanderdonckt, J., Leiva, L. A., Arapakis, I., Vakalellis, M., & Prevelakis, V. (2024). Adaptive Visualization Framework for Human-Centric Data Interaction in Time-Critical Environments. Proceedings of IHIET-AI 2024. Published. 11th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications, Lausanne, Switzerland. https://doi.org/10.54941/ahfe1004578