AHFE Open AccessAdaptive Visualization Framework for Human-Centric Data Interaction in Time-Critical Environments
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.
Keywords: Visualization, Human Interaction, AI-based Adaptive systems
DOI: 10.54941/ahfe1004578
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