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20212025
most citedLeveraging Machine Learning for Industrial Wireless Communications

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2025

Cloud-Fog Automation: The New Paradigm towards Autonomous Industrial Cyber-Physical Systems

Jiong Jin, Zhibo Pang, Jonathan Kua +4

Autonomous Industrial Cyber-Physical Systems (ICPS) represent a future vision where industrial systems achieve full autonomy, integrating physical processes seamlessly with communi…

cs.NI2023

Convergence of Manufacturing and Networking in Future Factories

Ilaria Malanchini, Nicola Michailow, Patrick Agostini +8

The roll out of 5G has been mainly characterized by its distinct support for vertical industries, especially manufacturing. Leveraging synergies among these two worlds, namely prod…

cs.NI2022

HARU: Haptic Augmented Reality-Assisted User-Centric Industrial Network Planning

Qi Liao, Tianlun Hu, Nikolaj Marchenko +2

To support Industry 4.0 applications with haptics and human-machine interaction, 6G requires a new framework that is fully autonomous, visual, and interactive. In this paper, we pr…

eess.SY2021

Age of Loop for Wireless Networked Control Systems Optimization

Pedro M. de Sant Ana, Nikolaj Marchenko, Petar Popovski +1

Joint design of control and communication in Wireless Networked Control Systems (WNCS) is a promising approach for future wireless industrial applications. In this context, Age of…

cs.NI2021★ 4 cited

Leveraging Machine Learning for Industrial Wireless Communications

Ilaria Malanchini, Patrick Agostini, Khurshid Alam +10

Two main trends characterize today's communication landscape and are finding their way into industrial facilities: the rollout of 5G with its distinct support for vertical industri…