The increasing need for economic, safe, and sustainable smart manufacturing combined with novel technological enablers, has paved the way for Artificial Intelligence (AI) and Big Data in support of smart manufacturing. 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 industries. In this paper, we provide a comprehensive overview of different aspects of AI and Big Data in Industry 4.0 with a particular focus on key applications, techniques, the concepts involved, key enabling technologies, challenges, and research perspective towards deployment of Industry 5.0. In detail, we highlight and analyze how the duo of AI and Big Data is helping in different applications of Industry 4.0. We also highlight key challenges in a successful deployment of AI and Big Data methods in smart industries with a particular emphasis on data-related issues, such as availability, bias, auditing, management, interpretability, communication, and different adversarial attacks and security issues. In a nutshell, we have explored the significance of AI and Big data towards Industry 4.0 applications through panoramic reviews and discussions. We believe, this work will provide a baseline for future research in the domain.
Human-Centric Artificial Intelligence Architecture for Industry 5.0 Applications
Qlector d.o.o.（Qlector有限公司）；Ubitech Ltd（Ubitech有限公司）；University of West Attica（西阿提卡大学）；R2M Solution Srl（R2M解决方案股份公司）；University of Cagliari（卡利亚里大学）；University of Piraeus（比雷埃夫斯大学）；National Technical University of Athens（雅典国立技术大学）；INTRASOFT International（INTRASOFT国际公司）；German Research Center for Artificial Intelligence (DFKI)（德国人工智能研究中心（DFKI））
Big Data Analytics for Manufacturing Internet of Things: Opportunities, Challenges and Enabling Technologies
Macau University of Science and Technology（澳门科技大学）；Norwegian University of Science & Technology（挪威科技大学）；Tianjin University（天津大学）；South China University of Technology（华南理工大学）；King Saud University（沙特国王大学）
City electric power consumption forecasting based on big data & neural network under smart grid background
School of Computer Science & Technology, Beijing Institute of Technology（北京理工大学计算机科学与技术学院）；University of Nottingham（诺丁汉大学）；School of Aeronautics and Astronautics, Tsinghua University（清华大学航空航天学院）
Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models
ENN Group Co.,Ltd.（ENN集团有限公司）；China University of Petroleum（中国石油大学）；Unicom (Shanghai) Industrial Internet Co.,Ltd.（联通（上海）工业互联网有限公司）；Qingdao Windaka Technology Co.,Ltd.（青岛Windaka科技有限公司）
