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Guest Editorial: Cognitive Analytics of Social Media for Industrial Manufacturing

Ali Kashif Bashir, Shahid Mumtaz, Varun G. Menon, Kim Fung Tsang
2021 IEEE Transactions on Industrial Informatics  
In the CC of intelligent IIoT, clustering is a fundamental machine learning problem to exploit latent data relationships.  ...  The authors showed the accuracy of the model through two artificial networks. Cognitive computing (CC) is emerging in several IIoT domains.  ... 
doi:10.1109/tii.2020.3028762 fatcat:t7ghwwqy2nb3llnaghl4b6a4mq

The Emergence of Artificial Intelligence for Industrial Internet of Thing Engagement

2021 International Journal of Advanced Trends in Computer Science and Engineering  
computing, big data, artificial intelligence and machine learning.  ...  Internet of Things & Artificial Intelligence are poised to transform industrial operations.  ...  The foundation of IoT is machine learning and artificial intelligence because it allows these devices to make sense of the data collected through them.  ... 
doi:10.30534/ijatcse/2021/121022021 fatcat:5jc6yqjjsvfx5m25zxuzcqi2wq

Editorial: Cognitive Industrial Internet of Things

Long Hu, Daxin Tian, Kai Lin
2018 Journal on spesial topics in mobile networks and applications  
Cognitive-IIoT provides high performance of communicating, computing, controlling, and even high degree of machine intelligence for emerging smart industrial IoT applications, such as cognitive manufacturing  ...  Cognitive Industrial Internet of Things (Cognitive-IIoT) is the use of cognitive computing technologies, which is derived from cognitive science and artificial intelligence, to power next generation Industrial  ...  Long Hu is an assistant professor in School of Computer Science and Technology at Huazhong University of Science and Technology  ... 
doi:10.1007/s11036-018-1115-y fatcat:nimwoztjbrdnznauphzjd7r23m

Internet of Robotic Things Intelligent Connectivity and Platforms

Ovidiu Vermesan, Roy Bahr, Marco Ottella, Martin Serrano, Tore Karlsen, Terje Wahlstrøm, Hans Erik Sand, Meghashyam Ashwathnarayan, Micaela Troglia Gamba
2020 Frontiers in Robotics and AI  
The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and "things" have evolved significantly.  ...  The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms  ...  AI adds value through machine learning capabilities, and IoT adds value to AI through connectivity, signaling, and data exchange.  ... 
doi:10.3389/frobt.2020.00104 pmid:33501271 pmcid:PMC7805974 fatcat:oejpeyynjndnxcq7jsdcotv7ua

Edge Intelligence for Data Handling and Predictive Maintenance in IIOT

Taimur Hafeez, Lina Xu, Gavin McArdle
2021 IEEE Access  
Before ML was used in IIoT, cognitive ability (to learn the environment) of the machines was merely predefined heuristics. However, [30] .  ...  The following section examine recent efforts to increase intelligence at the edge through the use of ML.  ... 
doi:10.1109/access.2021.3069137 fatcat:htkvpzsssbe5rdbxxevqenmuc4

The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions [article]

Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Kashif Ahmad, Ala Al-Fuqaha, Mohsen Guizani
2021 arXiv   pre-print
This implies a substantial integration of AI, Industrial Internet of Things (IIoT), Robotics, Big data, Blockchain, 5G communications, in support of smart manufacturing and the dynamical processes in modern  ...  In a nutshell, we have explored the significance of AI and Big data towards Industry 4.0 applications through panoramic reviews and discussions.  ...  ACKNOWLEDGMENT The authors gratefully acknowledge the Management, and Faculty of Mepco Schlenk Engineering College, Sivakasi, India for their support and extending necessary facilities to carry out this  ... 
arXiv:2104.02425v2 fatcat:r25gug6wmrbyjnreiewprdvqpa

The value chain of Industrial IoT and its reference framework for digitalization [article]

Hang Song, Yuncheng Jiang
2020 arXiv   pre-print
When Industrial IoT (IIoT) is concerned about, the enormous innovation potential of IoT technologies are not only in the production of physical devices, but also in all activities performed by manufacturing  ...  It is also known that IIoT acquire and analyze data from connected devices, Cyber-Physical Systems (CPS), locations and people (e.g. operator); along with its contemporary new terms, such as 5G, Edge computing  ...  Acknowledgments The content of this paper is largely relying on the contributions of the IoT workgroup of National University of Defense Technology.  ... 
arXiv:2009.13039v1 fatcat:e44mrtb4kzatvdthzz7fih3mka

Guest Editorial: Special Issue on Blockchain and Edge Computing Techniques for Emerging IoT Applications

Victor C. M. Leung, Xiaofei Wang, F. Richard Yu, Dusit Niyato, Tarik Taleb, Sangheon Pack
2021 IEEE Internet of Things Journal  
Focusing on the research of social-aware cloud computing, cooperative cell caching, and mobile traffic offloading, he has authored over 100 technical papers in  ...  Blockchain for Edge Intelligence The six articles in this group, which address various applications of blockchain for edge intelligence and explore the issues on robust routing, resource allocation, learning  ...  A smart contract is designed within a private blockchain network that exploits the state-of-the-art machine learning algorithm, asynchronous advantage actor-critic (A3C), to allocate the edge computing  ... 
doi:10.1109/jiot.2021.3050050 fatcat:rux57gjppjdqla556myxnvp4ve

Q-Learning-Based Dynamic Spectrum Access in Cognitive Industrial Internet of Things

Feng Li, Kwok-Yan Lam, Zhengguo Sheng, Xinggan Zhang, Kanglian Zhao, Li Wang
2018 Journal on spesial topics in mobile networks and applications  
In this paper, we propose a Q-learning-based dynamic spectrum access method for IIoT by introducing cognitive self-learning technical solution to solve the difficulty of distributed and ordered self-accessing  ...  In recent years, Industrial Internet of Things (IIoT) has attracted growing attention from both academia and industry.  ...  Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution  ... 
doi:10.1007/s11036-018-1109-9 fatcat:py5zaqpbwnbrlisdsyak6tmnzq

AI-Inspired Non-Terrestrial Networks for IIoT: Review on Enabling Technologies and Applications

Emmanouel T. Michailidis, Stelios M. Potirakis, Athanasios G. Kanatas
2020 IoT  
In this regard, this paper sheds light on the potential role of artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL), in the provision of challenging NTN-based  ...  IIoT services and provides a thorough review of the relevant research works.  ...  Among these techniques, machine learning (ML) [96] , a subset of AI, consists of supervised and unsupervised learning, as well as reinforcement learning (RL), and can improve the performance of a system  ... 
doi:10.3390/iot1010003 fatcat:xkjxfh6r2fd27jyuxazfc6lbqu

A Review of 4IR/5IR Enabling Technologies and Their Linkage to Manufacturing Supply Chain

Mokesioluwa Fanoro, Mladen Božanić, Saurabh Sinha
2021 Technologies  
Most factory activities have been transformed through a set of features built into a smart manufacturing framework.  ...  The manufacturing supply chain is envisaged as enhancing the enabling technologies of Industry 4.0 through their integration.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/technologies9040077 fatcat:cq6odciabrbvnccqbv4vnl7jze

Deep Learning in Industrial Internet of Things: Potentials, Challenges, and Emerging Applications [article]

Ruhul Amin Khalil, Nasir Saeed, Yasaman Moradi Fard, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini
2020 arXiv   pre-print
These enormous number of IoT devices generates a large capacity of data that further require intelligent data analysis and processing methods, such as Deep Learning (DL).  ...  Therefore, motivated by these numerous applications; in this paper, we present the key potentials of DL in IIoT.  ...  This way, the learning process for various industrial devices will improve, resulting in an intelligent IIoT network with low computational complexity and improved network lifetime.  ... 
arXiv:2008.06701v1 fatcat:2kp64xhxhjcojegff3aul4keee

Active Learning based Laboratory towards Engineering Education 4.0

Miguel Delgado Prieto, Angel Fernandez Sobrino, Lucia Ruiz Soto, David Romero, Pere Fibla Biosca, Luis Romeral Martinez
2019 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)  
This approach tries to build up an enhanced interaction environment between human intelligence and cognitive abilities of artificial intelligence based systems.  ...  second, the leadership in the advance of knowledge through scientific research, and third, the transfer of knowledge and experience towards society to improve the quality of life [2] .  ... 
doi:10.1109/etfa.2019.8869509 dblp:conf/etfa/PrietoSSRBM19 fatcat:2anpnpo4lvd4bmrzxuuusibeoy

Integral Support Predictive Platform for Industry 4.0

Sergio Márquez Sánchez
2020 Advances in Distributed Computing and Artificial Intelligence Journal  
the new sources of information, solutions and Industrial Internet of Things (IIoT) devices that may be implemented.  ...  This work seeks to provide a reference software architecture at the service of the connected industry that allows the provision of new capacities for process optimisation, predictive maintenance and real-time  ...  ability.  ... 
doi:10.14201/adcaij2020947182 fatcat:27z6cpnnxrekja5t77epxkrxyq

Scalable Fleet Monitoring and Visualization for Smart Machine Maintenance and Industrial IoT Applications

Pieter Moens, Vincent Bracke, Colin Soete, Sander Vanden Hautte, Diego Nieves Avendano, Ted Ooijevaar, Steven Devos, Bruno Volckaert, Sofie Van Hoecke
2020 Sensors  
The resulting platform provides benchmark data for the improvement of machine learning algorithms, gives insights into the design, implementation and validation of a complete architecture for IIoT applications  ...  Furthermore, effective application of predictive maintenance requires well-trained machine learning algorithms which on their turn require high volumes of reliable data.  ...  Acknowledgments: We would like to thank Nathan Vandemoortele for his contribution to the machine learning algorithms for prediction of the remaining useful life and Jasper Vaneessen for his contribution  ... 
doi:10.3390/s20154308 pmid:32748809 pmcid:PMC7435597 fatcat:rimk2uxpkzd7havtrz6oo3bwau
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