This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.

This proceedings of the International Congress and Workshop on Industrial AI 2021 encompasses and integrates the themes and topics of three conferences, eMaintenance, Condition Monitoring and Diagnostic Engineering management (COMADEM), and Advances in Reliability, Maintainability and Supportability (ARMS) into a single resource. The 21st century is witnessing the emerging extensive applications of Artificial Intelligence (AI) and Information Technologies (IT) in industry. Industrial Artificial Intelligence (IAI) integrates IT with Operational Technologies (OT) and Engineering Technologies (ET) to achieve operational excellence through enhanced analytics in operation and maintenance of industrial assets. This volume provides insight into opportunities and challenges caused by the implementation of AI in industries apart from future developments with special reference to operation and maintenance of industrial assets. Industry practitioners in the maintenance field as well as academics seeking applied research in maintenance will find this text useful.

This proceedings brings together the papers presented at the International Congress and Workshop on Industrial AI and eMaintenance 2023 (IAI2023). The conference integrates the themes and topics of three conferences: Industrial AI & eMaintenance, Condition Monitoring and Diagnostic Engineering Management (COMADEM) and, Advances in Reliability, Maintainability and Supportability (ARMS) on a single platform. This proceedings serves both academy and industry in providing an excellent platform for collaboration by providing a forum for exchange of ideas and networking. The 21st century has seen remarkable progress in Artificial Intelligence, with application to a variety of fields (computer vision, automatic translation, sentiment analysis in social networks, robotics, etc.) The IAI2023 focuses on Industrial Artificial Intelligence, or IAI. The emergence of industrial AI applications holds tremendous promises in terms of achieving excellence and cost-effectiveness in the operation and maintenance of industrial assets. Opportunities in Industrial AI exist in many industries such as aerospace, railways, mining, construction, process industry, etc. Its development is powered by several trends: the Internet of Things (IoT); the increasing convergence between OT (operational technologies) and IT (information technologies); last but not least, the unabated fast-paced developments of advanced analytics. However, numerous technical and organizational challenges to the widespread development of industrial AI still exist. The IAI2023 conference and its proceedings foster fruitful discussions between AI creators and industrial practitioners.

Presents compendium of methodologies and technologies in industrial AI and digitalization Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept Covers a broad range of academic and industrial issues within the field of asset management Discusses impact of Industry 4.0 in other sectors Includes a dedicated chapter on real-time case studies

Amid the dynamic growth of artificial intelligence, this book presents a collection of findings and advancements from the second edition of the A2IA-Artificial Intelligence and Industrial Applications conference. The conference, hosted by ENSAM-Meknès at Moulay Ismail University, Morocco, fosters knowledge exchange in AI, focusing primarily on its industrial applications. Covering a wide range of topics, the book highlights the adaptable nature of AI and its increasing impact on industrial sectors. It brings together contributions from an international cohort of researchers, discussing themes such as intelligent manufacturing and maintenance, intelligent supply chain management, various modes of learning including supervised, unsupervised, reinforcement, semi-supervised, and graph-based, as well as neural networks, deep learning, planning, and optimization. A defining feature of this edition is its extensive scope and emphasis on the practical applications of AI, along with its foundational elements. It facilitates an understanding of AI's current state and potential future direction, showcasing recent developments that bridge the gap between theory and practice. Designed for a diverse readership, this book is of interest to AI practitioners, academics, and enthusiasts, as well as to those new to the field. It provides an opportunity to explore AI's critical role in industrial applications, and the practical insights it offers are likely to be beneficial for decision-making within industrial settings.

This book begins by discussing the fundamentals of Artificial Intelligence, the Internet of Things, and their convergence. It then covers techniques, algorithms, and methods of analysing and processing data over the Artificial Intelligence of Things. The text elaborates on important concepts such as body sensor networks for safety in smart factories, smart energy management, smart robotic assistive systems, and service-oriented smart manufacturing. This book: • Discusses the security and privacy aspect of Artificial Intelligence of Things (AIoT) for smart real-time applications. • Explores challenges and issues of Artificial Intelligence and the Internet of Things in the field of industrial automation. • Includes case studies in Artificial Intelligence of Things (AIoT) convergence for data processing. • Showcases algorithms, techniques, and methods of analysing and processing data over the Artificial Intelligence of Things. • Highlights operation management using human-robot, smart maintenance, and autonomous production. It will serve as an ideal reference text for senior undergraduate, graduate students, and professionals in fields including industrial engineering, production engineering, manufacturing engineering, operations research, and computer engineering.

The ever-evolving industrial landscape poses challenges for businesses, particularly in robotics, where performance optimization and data security are paramount. AI and Blockchain Applications in Industrial Robotics, edited by esteemed scholars Mihai Lazarescu, Rajashekhar Biradar, Geetha Devanagavi, Nikhath Tabassum, and Nayana Hegde, presents the transformative potential of combining AI and blockchain technologies to revolutionize the field. This exceptional book provides comprehensive insights into how AI enhances predictive models and pattern recognition, while blockchain ensures secure and immutable data transactions. By synergizing these technologies, businesses can achieve enhanced transparency, trust, and efficiency in their robotic processes. With practical applications, use cases, and real-world examples, the book caters to a wide range of readers, empowering them to embrace the possibilities of AI and blockchain in industrial robotics. AI and Blockchain Applications in Industrial Robotics equip industries with the tools and understanding to overcome challenges in optimizing performance, ensuring data security, and harnessing emerging technologies. Serving as a beacon of knowledge, this book drives innovation, efficiency, and competitiveness in the industrial sector. Whether for postgraduate students, researchers, industry professionals, undergraduate students, or freelance developers, the book provides valuable insights and practical guidance for implementing AI and blockchain solutions. By embracing the transformative potential of these technologies, industries can unlock new possibilities and propel themselves forward in the ever-advancing world of industrial robotics.

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments. The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency. A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.

The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike.

This double volume book set constitutes the refereed proceedings of 4th International Conference, AI-HCI 2023, held as part of the 25th International Conference, HCI International 2023, which was held virtually in Copenhagen, Denmark in July 2023. The total of 1578 papers and 396 posters included in the HCII 2023 proceedings was carefully reviewed and selected from 7472 submissions. The first volume focuses on topics related to Human-Centered Artificial Intelligence, explainability, transparency and trustworthiness, ethics and fairness, as well as AI-supported user experience design. The second volume focuses on topics related to AI for language, text, and speech-related tasks, human-AI collaboration, AI for decision-support and perception analysis, and innovations in AI-enabled systems.