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IssuesSpecial Issues
Human-centric Computing and Information Sciences (HCIS) Korea Information Processing Society-Computer Software Research Group (KIPS-CSWG)(ISSN: 2192-1962)

(IF 5.900) Special issue on

AI-Empowered Smart Sensing for Next Generation Industrial CPSs

The proliferation of industrial Cyber-Physical Systems (CPSs), including Internet of Things (IoT), is changing our lives. The path towards next generation industrial CPSs is characterized by several steps, among which the Smart Sensing (SS) is fundamental. SS embedded into industrial CPSs are widely used to collect environmental parameters in homes, buildings, vehicles, etc., where they are used as a source of information that aids the decision-making process and, in particular, it allows systems to learn and to monitor activity. At the same time, AI is becoming an integral part of industrial CPSs that can automate and improve a wide range of municipal activities and operations via some advanced technologies such as data mining, machine learning, deep learning, and data science, etc. Thus, the integration of SS and AI will drive the industrial CPSs technology revolution. AI-empowered SS will allow multivariate sensing on one sensor node, miniature sensing that provides accessibility to monitor complex structure and achieve low-power data transmission. Moreover, with the help of advanced AI technologies, we are able to discover new techniques and knowledge from complex sensor datasets in next generation industrial CPSs, which can promote product innovation, improves security level and efficiency of smart cities, and expand novel business models.

The aim of this special issue is to stimulate discussions on the design, use, and evaluation of AI-empowered SS solutions for next generation industrial CPSs. However, when integrating these two technologies, there are still some open issues, such as security and efficiency, accuracy, privacy, data trustworthiness and quality, and participation motivation & incentive that need to be addressed. This special issue will bring together academics and industrial practitioners to exchange and discuss the latest innovations and applications of AI in the domain of SS for next generation industrial CPSs.

The topics of interest include, but are not limited to:

SS networks using AI for industry 4.0

AI and machine learning in SS networks for healthcare

Machine learning platform for big data-driven smart traffic management

AI-based sensor platforms for the IoT in smart cities

AI-based multi sensor fusion for smart decision making

AI-based cloud computing application for smart home

AI empowered context-aware smart system

Machine learning enabled smart sensor systems

Deep and reinforcement learning for IoT

Integration of AI and IoT into industrial CPSs

Applying AI and IoT to industrial scenarios

Any novel methods and applications of SS and AI for CPSs

Important Deadlines

Open submission: 5 Nov. 2021

Submission deadline: 28 Feb. 2022

Author notification: within 4 weeks after submission

Revised manuscript due: within 2 weeks after notification

Notification of acceptance: within 2 weeks after revision submission

Tentative accepted paper publication date: within 2 months after final version

Tentative SI paper collection and its web open: 2nd / 3rd Quarter, 2022 (TBA)

Submission Guideline

All submitted papers must be clearly written in excellent English and contain only original work. All papers must be submitted in an electronic format, e.g., PDF format (preferred) or MS Word. Manuscripts should follow the formatting of the sample manuscript and references. You can refer to the details in the submission menu http://hcisj.com/submission/preparing_manuscript.php.
All papers and some supplementary materials should be submitted through ScholarOne Manuscripts. The authors must select “SI2021-06 AI-Empowered Smart Sensing”. when they reach the “Article Type” step in the submission process https://mc04.manuscriptcentral.com/hcis

Guest Editors

Dr. Syed Hassan Ahmed, JMA Wireless, USA. sh.ahmed@ieee.org (Lead GE).

Dr. Shahid Mumtaz, Instituto de Telecomunicações, Portugal. smumtaz@av.it.pt

Dr. Wei Wang, Sun Yat-sen University, China. wangw328@mail.sysu.edu.cn