Web Based Data Visualization Dashboard for Sensor and Pose Estimation Data
Abstract
Our proposed visual dashboard aims to facilitate training progress evaluation in sports like skateboarding and foil pumping by offering real-time sensor and camera data processing through machine learning-based pose estimation. The web-based application, developed in HTML, CSS, and JavaScript utilizing p5js and Google Charts frameworks, enables athletes to visualize and analyze their movements for efficient and safe performance without the need for app installation on various devices. This paper will delve into the advantages and challenges of the web-based approach, detailing data structures, synchronization techniques, and plans for future enhancements like Web BLE connectivity and improved user experience across different devices.
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| Titel | Web Based Data Visualization Dashboard for Sensor and Pose Estimation Data |
|---|---|
| Medien | International Conference on Human-Computer Interaction |
| Verlag | Springer Nature Switzerland |
| Heft | --- |
| Band | --- |
| ISBN | --- |
| Verfasser/Herausgeber | Prof. Michael Zöllner, Moritz Krause |
| Seiten | 291-296 |
| Veröffentlichungsdatum | 06.01.2024 |
| Projekttitel | --- |
| Zitation | Zöllner, Michael; Krause, Moritz (2024): Web Based Data Visualization Dashboard for Sensor and Pose Estimation Data. International Conference on Human-Computer Interaction, S. 291-296. DOI: 10.1007/978-3-031-62110-9_31 |