Date: Oct. 19-21, 2022
IMPORTANT DATES
Same as ICTC2022 regular paper (https://ictc.org/).

This workshop is to address the latest trends of research and visions for industrial networks. The topics covered in the workshop include data processing and analysis, communication and control design for industrial networks, the use of artificial intelligence and machine learning for industrial networks including multi-agent learning and edge intelligence, and experiment studies using industrial networks (e.g., for smart factory/city/building/farm, etc.).

It is expected that B5G communication significantly impacts on how industrial networks are deployed, managed and operated. While industrial networks have stringent requirements in delays, massive connectivity, and scalability, data-driven approaches based on machine learning are expected to be adopted to manage various requirements of industrial networks using 5G and beyond 5G wireless communication. In particularly, due to limited communication resources for data transmission, distributed learning frameworks would be required where the wireless devices collaboratively build a shared learning model with training their collected data locally. This workshop aims to bring together academic and industrial researchers in an effort to identify and discuss the major challenges and recent breakthroughs related to industrial networks and the use of machine learning. Considering that there have been a lot of studies in smart factory, the outcome of experiment studies are also expected to be discussed.

Topics of interest include, but are not limited to the following.

• Data Processing and Analysis for Industrial Network Communication
• Fundamental Trade-offs and Communication Protocols for Reliable Communication in Industrial Networks
• Enhancements for Industrial Communication, Including Architectures and Interworking of Public and Private Networks
• Communication for Unmanned Aerial Vehicles (UAVs), Robot Fleets, and Automated Guided Vehicles (AGVs) in Industrial Manufacturing Environments
• Exploiting Artificial Intelligence (AI) and Machine Learning (ML) Techniques for Industrial IoT and Ultra-reliable Communication
• Network Architectures and Communication Protocols for Edge Learning in Industrial Networks
• Multi-agent Reinforcement Learning for Intelligent Control and Optimization
• Performance Prediction and Monitoring of Industrial Networks
• Experimental Verification & Technology Trial Results in Factory Automation and Process Automation Using Industrial Networks

• Klaus Moessner (Technische Universität Chemnitz, klaus.moessner@etit.tu-chemnitz.de)
• Chuan Heng Foh (Univ. of Surrey, c.foh@surrey.ac.uk)
• Haeyoung Lee (University of Surrey, Haeyoung.Lee@surrey.ac.uk)

• Sajin Kim (IITP, sj.kim@iitp.kr)
• Seungwoo Keum (KETI, swkum@keti.re.kr)
• Jaewon Moon (KETI, jwmoon@keti.re.kr)
• Pilsung Kang (Korea University, pilsung_kang@korea.ac.kr)
• Yannick Carlinet (Orange Innovation, yannick.carlinet@orange.com)
• Mikko Uitto (VTT, Mikko.Uitto@vtt.fi)
• Mickael Maman (CEA-LETI, mickael.maman@cea.fr)

ICTC 2022 workshops invite the submission of original, unpublished research work (including position papers) that is not currently under review elsewhere.

Authors are invited to submit 6-page full paper or a 3-page short paper electronically as PDF files through EDAS. The direct link for paper submission is https://edas.info/newPaper.php?c=29556. The submissions should be formatted with single-spaced, double-column pages using at least 10 pt size fonts on A4 or letter pages in IEEE conference style. The direct link for the IEEE template is https://www.ieee.org/conferences/publishing/templates.html

All papers must be submitted via EDAS in the PDF format. Authors can refer to the submission guideline for EDAS at https://edas.info/doc/authors.html. Authors may receive one or more of the error messages while they upload their manuscript. In such a case, please check the EDAS FAQ at https://edas.info/listFAQ.php

Online submission: https://edas.info/newPaper.php?c=29556