Realizing Immersive Communications in Human Digital Twin by Edge Computing Empowered Tactile Internet: Visions and Case Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human digital twin (HDT) is expected to revolutionize the future human lifestyle and prompt the development of advanced human-centric applications (e.g., Metaverse) by bridging physical and virtual spaces. However, the fulfillment of HDT poses stringent demands on the pervasive connectivity, real-time feedback, multi-modal data transmission and ultra-high reliability, which urge the need of enabling immersive communications. In this article, we shed light on the design of an immersive communication framework for HDT by edge computing empowered tactile Internet (namely IC-HDT-ECoTI). Aiming at offering strong interactions and extremely immersive quality of experience, we introduce the system architecture of IC-HDT-ECoTI, and analyze its major design requirements and challenges. Moreover, we present core guidelines and detailed steps for system implementations. In addition, we conduct an experimental study based on our recently built testbed, which shows a particular use case of IC-HDT-ECoTI in physical therapy, and the obtained results indicate that the proposed framework can significantly improve the effectiveness of the system. Finally, we conclude this article with a brief discussion of open issues and future directions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it