Gaze Insights in XR: Real-Time Eye-Tracking Analytics with Elasticsearch

Gaze tracking serves as a critical component in human-computer interaction, significantly enhancing the capabilities of immersive extended-reality (XR) applications. Despite the integration of advanced eye-tracking technologies in modern XR devices, challenges surrounding usability, scalability, and privacy remain unresolved. This study presents a technical framework leveraging the Elastic Stack (Elasticsearch, Logstash, Kibana) to enable real-time data collection, indexing, and analysis of gaze-tracking data alongside other interaction metrics. The framework integrates scalable distributed storage, efficient querying, and immersive heatmap visualizations within Unity, offering precise insights into user gaze behavior during interactive tasks. A pilot study involving a gaze-intensive VR task validated the system’s capacity to identify focus regions, analyze attention shifts, and detect performance bottlenecks. Notable functionalities include real-time heatmap overlays for user engagement analysis and replay systems for assessing spatial navigation strategies. The framework employs secure indexing configurations to address ethical concerns and discusses privacy-preserving mechanisms, including homomorphic encryption, ensuring the protection of sensitive data such as user focus and intent. This pilot provides a robust, scalable, and privacy-compliant solution for gaze-driven analytics, advancing the state of usability studies and XR application development.