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Scalable Coordinated Learning for H2M/R Applications over Optical Access Networks (Invited)

Networking and Internet Architecture 2025-03-03 v1 Artificial Intelligence

Abstract

One of the primary research interests adhering to next-generation fiber-wireless access networks is human-to-machine/robot (H2M/R) collaborative communications facilitating Industry 5.0. This paper discusses scalable H2M/R communications across large geographical distances that also allow rapid onboarding of new machines/robots as 72%\sim72\% training time is saved through global-local coordinated learning.

Keywords

Cite

@article{arxiv.2502.20598,
  title  = {Scalable Coordinated Learning for H2M/R Applications over Optical Access Networks (Invited)},
  author = {Sourav Mondal and Elaine Wong},
  journal= {arXiv preprint arXiv:2502.20598},
  year   = {2025}
}

Comments

This article is accepted for publication in 29th Opto-Electronics and Communications Conference 2024 (OECC2024). Copyright @ IEEE

R2 v1 2026-06-28T22:00:59.598Z