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AI-Empowered Internet of Things for Next Generation Industrial CPSs

AI-Empowered Internet of Things for Next Generation Industrial CPSs

Journal
Impact Score 5.45

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Special Issue Information

Submission Deadline: 15-12-2021
Journal Impact Score: 5.45
Journal Name: Computer Communications
Publisher: Computer Communications

Special Issue Call for Papers


Special Issue on



AI-Empowered Internet of Things for Next Generation Industrial CPSs



Justification



Industrial Cyber Physical Systems (CPSs) aim to conduct pre-competitive research on architectures and design, modeling, and analysis techniques for cyber-physical systems, with emphasis on industrial applications. These applications include transportation systems, automation, security, smart buildings, smart cities, medical systems, energy generation and distribution, water distribution, agriculture, military systems, process control, asset management, and robotics. Recently, the emergence of embedded and ubiquitous cyber-physical applications has driven the evolution of industrial CPSs. One of the key enablers for future industrial CPSs is the Internet of Things (IoT), which can exploit state-of-the-art communication technologies to support advanced services. However, IoT devices and management systems are typically manufactured by multiple vendors with multiple processes and standards. Furthermore, these devices will generate large amounts of data from different sources and types of sensors, which cannot be effectively processed by traditional methods. In addition, the unstructured data in IoT plays an important role in building next generation industrial CPSs, while transmitting and processing these unstructured data consume substantial energy. Therefore, data transmission and processing in IoT for CPSs should be performed in a more intelligent manner. Recently, Artificial Intelligence (AI) has recently emerged as a powerful weapon that supports very implement efficient data analysis and make accurate decisions on service provisions in various kinds. Combining IoT with advanced AI technology will drive the industrial CPSs technology revolution. AI-Empowered solutions, such as deep learning and reinforcement learning, can better process the vast amounts of real-time data that stream from IoT devices to support intelligent services for industrial informatics. In light of this potential, this special section provides a venue to cover comprehensively algorithms, frameworks, technologies, and applications of AI-empowered Internet of Things for next generation industrial CPSs.



There has been an emerging trend to take AI and IoT into consideration when researching Industry 4.0. Although some attempts have been done, there exist various scientific and engineering challenges including software and hardware development, computational complexity, data multi-source heterogeneity, and privacy protection. This special issue focuses on the crossroads among scientists, industry practitioners, and researchers from diverse domains in IoT, data mining, complex network, mobile computing, AI, industrial internet, smart cities, etc. This special issue aims to solicit high-quality original research papers, which address the cutting-edge theories, models, and applications for next generation industrial CPSs, supported by advanced AI empowered IoT technologies.



Topics of interest includes, but not limited to:




Tentative Schedule:



Submissions Deadline: July 31, 2021



First Reviews Due: September 15, 2021



Revision Due: October 31, 2021



Acceptance Notification: November 30, 2021



Final Manuscript Due: December 15, 2021



Publication Date: 2021




Guest Editor



Dr. Wei Wang
University of Macau, Macau SAR
Email: [email protected]
Google Scholar: https://scholar.google.com/citations?user=ydua3iAAAAAJ&hl=en



Wei Wang is a Research Fellow at University of Macau, Macau SAR. He received PhD degree in software engineering from Dalian University of Technology in 2018. His research interests include computational social science, data mining, internet of things, and artificial intelligence. He has authored/co-authored over 40 scientific papers in international journals and conferences, i.e., IEEE Internet of Things, IEEE Transactions on Industrial Informatics, IEEE Transactions on Big Data, IEEE Transactions of Emerging Topics in Computing, IEEE Transactions on Human-Machine Systems, The Web Conference, etc. He is the Leading Guest Editor of International Journal of Distributed Sensor Networks and Wireless Communication & Mobile Computing. He is the guest editor of ACM Transactions on Internet Technology, IEEE Journal of Biomedical and Health Informatics, and Computer Networks. He is a PC member of International Conference on Smart Internet of Things 2019/2020 and regular reviewer of IEEE Communications Magazine, Future Generation Computer Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Big Data, and IEEE Transactions of Emerging Topics in Computing, etc. He is a member of IEEE, ACM, and CCF.



Dr. Vincenzo Piuri (Fellow, IEEE)
University of Milan, Italy
Email: [email protected]
Google Scholar: https://scholar.google.com/citations?user=cAaTvfcAAAAJ&hl=en&oi=ao



Vincenzo PIURI received his Ph.D. in computer engineering Politecnico di Milano, Italy, 1989. He was Associate Professor at Politecnico di Milano, Italy (1992-2000) and Visiting Professor at the University of Texas at Austin (summers 1996-1999). He is Full Professor in computer engineering (since 2000) and Director of the Department of Information Technology (2007-12) at the Università degli Studi di Milano, Italy. His main research interests are: biometrics, signal and image processing, pattern analysis and recognition, theory and industrial applications of neural networks, machine learning, intelligent measurement systems, industrial applications, fault tolerance, digital processing architectures, embedded systems, cryptographic architectures, arithmetic architectures. He has participated in several national and international research projects funded by the European Union, the Italian Ministry of Research, the National Research Council of Italy, the Italian Space Agency, and industries. Original results have been published in more than 350 papers in international journals, proceedings of international conferences, and book chapters. He is Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He has been Associate Editor of the IEEE Transactions on Neural Networks and the IEEE Transactions on Instrumentation and Measurement. He has been President of the IEEE Computational Intelligence Society, Vice President for Publications of the IEEE Instrumentation and Measurement Society and the IEEE Systems Council, Vice President for Membership of the IEEE Computational Intelligence Society, and Vice President for Education of the IEEE Biometrics Council. He is IEEE Director (2010-12). He received the IEEE Instrumentation and Measurement Society Technical Award (2002) for the contributions to the advancement of theory and practice of computational intelligence in measurement systems and industrial applications, the IEEE Instrumentation and Measurement Society Distinguished Service Award (2008), and the IEEE Computational Intelligence Society Meritorious Service Award (2009).



Dr. Qingchen Zhang
St. Francis Xavier University, Canada
Email: [email protected]
Google Scholar: https://scholar.google.com/citations?user=jOQZJvYAAAAJ&hl=en&oi=ao



Dr. Qingchen Zhang is currently an assistant professor at the Department of Computer Science at St. Francis Xavier University. He got his doctoral degree from Dalian University of Technology in China, 2015. His research interests include big data, deep learning and smart medicine. He has published more than 20 papers on the topics of big data and deep learning—including papers in IEEE Transactions on Computers, IEEE Transactions on Services Computing, IEEE Transactions on Industrial Informatics, and so on. He served as a program chair of the 2015 IEEE Symposium on Smart Data, a program chair of IEEE International Conference on Pervasive, Intelligence and Computing (PICom 2016), and the leading program chair of IEEE International Conference on Internet of Things (iThings 2018). In addition, he is one of the guest editors of Future Generation Computer Systems special issue on Smart Data for Internet of Things, IEEE Access special session on cyber-physical-social computing and networking, Wireless Communications and Mobile Computing special issue on IoT Big Data Analytics, and so on.



Dr. Keping Yu
Waseda University, Japan
Email: [email protected]



Keping Yu received the M.E. and Ph.D. degrees from the Graduate School of Global Information and Telecommunication Studies, Waseda University, Tokyo, Japan, in 2012, and 2016, respectively. He was a Research Associate and a Junior Researcher with the Global Information and Telecommunication Institute, Waseda University, from 2015 to 2019 and from 2019 to 2020, respectively, where he is currently a Researcher. He has hosted and participated in more than ten projects, is involved in many standardization activities organized by ITU-T and ICNRG of IRTF, and has contributed to ITU-T Standards Y.3071 and Supplement 35. His research interests include smart grids, information-centric networking, the Internet of Things, blockchain, and information security. He was the Chair of the IEEE/CIC ICCC 2nd EBTSRA workshop, the General Co-Chair and the Publicity Co-Chair of the IEEE VTC2020-Spring EBTSRA workshop, the TPC Co-Chair of the SCML2020, the Local Chair of the MONAMI 2020, the Session Co-Chair of the CcS2020, and the Session Chair of the ITU Kaleidoscope 2016. He has served as a TPC Member for more than ten international conferences, including ITU Kaleidoscope, the IEEE Vehicular Technology Conference (VTC), the IEEE Consumer Communications and Networking Conference (CCNC), and the IEEE Wireless Communications and Networking Conference (WCNC). He has been a Lead Guest Editor for Sensors, Peer-to-Peer Networking and Applications.

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