This book brings together past insights, current research and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real-world problems. The book is based on the International Conference on Distributed Computing and Artificial Intelligence 2020 (DCAI 2020), which provided a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. It includes contributions on well-established and evolving areas of research, by authors from 26 countries, representing a truly “wide area network” of research activity

This book presents the outcomes of the 15th International Conference on Distributed Computing and Artificial Intelligence, held in Toledo (Spain) from 20th to 22nd June 2018 and hosted by the UCLM, and which brought together researchers and developers from industry, education and the academic world to report on the latest scientific research, technical advances and methodologies. Highlighting multi-disciplinary and transversal aspects, the book focuses on the conferences Special Sessions, including Advances in Demand Response and Renewable Energy Sources in Smart Grids (ADRESS); AI- Driven Methods for Multimodal Networks and Processes Modeling (AIMPM); Social Modelling of Ambient Intelligence in Large Facilities (SMAILF); Communications, Electronics and Signal Processing (CESP); Complexity in Natural and Formal Languages (CNFL); and Web and Social Media Mining (WASMM).

This book presents the outcomes of the special sessions of the 16th International Conference on Distributed Computing and Artificial Intelligence 2019, a forum that brought together ideas, projects and lessons associated with distributed computing and artificial intelligence, and their applications in various areas. Artificial intelligence is currently transforming our society. Its application in distributed environments, such as the internet, electronic commerce, environmental monitoring, mobile communications, wireless devices, and distributed computing, to name but a few, is continuously increasing, making it an element of high added value and tremendous potential. These technologies are changing constantly as a result of the extensive research and technical efforts being pursued at universities and businesses alike. The exchange of ideas between scientists and technicians from both the academic and industrial sectors is essential to facilitating the development of systems that can meet the ever-growing demands of today’s society. This year’s technical program was characterized by high quality and diversity, with contributions in both well-established and evolving areas of research. More than 120 papers were submitted to the main and special sessions tracks from over 20 different countries (Algeria, Angola, Austria, Brazil, Colombia, France, Germany, India, Italy, Japan, the Netherlands, Oman, Poland, Portugal, South Korea, Spain, Thailand, Tunisia, the United Kingdom and United States), representing a truly “wide area network” of research activity. The symposium was jointly organized by the Osaka Institute of Technology and the University of Salamanca. This year’s event was held in Avila, Spain, from 26th to 28th June, 2019. The authors wish to thank the sponsors: the IEEE Systems Man and Cybernetics Society, Spain Section Chapter and the IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA, APPIA and AIR institute.

The present book brings together experience, current work, and promising future trends associated with distributed computing, artificial intelligence, and their application in order to provide efficient solutions to real problems. DCAI 2023 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 108 papers were submitted, by authors from 31 different countries representing a truly “wide area network” of research activity. The DCAI’23 technical program has selected 50 full papers in the Special Sessions (ASET, AIMPM, AI4CS, CLIRAI, TECTONIC, PSO-ML, SmartFoF, IoTalentum) and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the LASI and Centro Algoritmi of the University of Minho (Portugal). The authors like to thank all the contributing authors, the members of the Program Committee, National Associations (AEPIA, APPIA), and the sponsors (AIR Institute).

This book addresses a broad range of topics, from newly proposed techniques in Artificial Intelligence (AI) and Machine Learning to various applications such as decision-making, pattern classification for data, image and signals, robotics, and control systems. Big data applications are discussed, while improved methods and wholly new methods for using deep learning technologies are also presented. The topics covered are comprehensive and reflect a wide range of technologies in the area. In particular, the latest methods in deep learning approaches and applications are discussed in many parts of the book, providing a better understanding of these new technologies. The book’s general scope includes the latest methods in the areas of Artificial Intelligence and Machine Learning for use in distributed computing as well as decision support systems. As the book covers a rather wide area, its intended readership ranges from those working in AI and machine learning technologies to those working on applications utilizing these technologies, researchers new to these areas who need background information on the technologies and applications, and more experienced researchers looking for new methods and applications.

This book brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. DCAI 2020 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 83 papers were submitted to main track and special sessions, by authors from 26 different countries representing a truly “wide area network” of research activity. The DCAI’20 technical program has selected 35 papers and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the University of L'Aquila (Italy). We would like to thank all the contributing authors, the members of the Program Committee and the sponsors (IBM, Armundia Group, EurAI, AEPIA, APPIA, CINI, OIT, UGR, HU, SCU, USAL, AIR Institute and UNIVAQ).

DCAI 2022 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 46 papers were submitted, by authors from 28 different countries representing a truly “wide area network” of research activity. The DCAI’22 Special Sessions technical program has selected 22 papers (12 full papers) and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the University of L'Aquila (Italy). We would like to thank all the contributing authors, the members of the Program Committee and the sponsors (IBM, Indra, Dipartimento di Ingegneria e Scienze dell'Informazione e Matematica dell'Università degli Studi dell'Aquila, Armundia Group, Whitehall Reply, T.C. Technologies And Comunication S.R.L., LCL Industria Grafica, AIR Institute, AEPIA, APPIA).

This book looks at industry change patterns and innovations (such as artificial intelligence, machine learning, big data analysis, and blockchain support and efficiency technology) that are speeding up industrial transformation, industrial infrastructure, biodiversity, and productivity. This book focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing. It also offers insights into manufacturing, logistics, and supply chain, where systems have undergone an industrial transformation. It discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure. It goes on to cover the effects that the Fourth Industrial Revolution has on industrial infrastructures and looks at the current industry change patterns and innovations that are accelerating industrial transformation activities. Researchers, scholars, and students from different countries will appreciate this book for its real-world applications and knowledge acquisition. This book targets manufacturers, industry owners, product developers, scientists, logistics, and supply chain engineers. Focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing Offers insights into manufacturing, logistics, and supply chain where systems have undergone an industrial transformation Discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure Covers the effects that the 4th Industrial Revolution has on industrial infrastructures Looks at industry change patterns and innovations that are speeding up industrial transformation activities Om Prakash Jena is currently working as an associate professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Sabyasachi Pramanik is an assistant professor in the Department of Computer Science and Engineering, Haldia Institute of Technology, India. Ahmed A. Elngar is an associate professor in the Faculty of Computers & Artificial Intelligence, Beni-Suef University, Egypt. He is also an associate professor in the College of Computer Information Technology, chair of the Scientific Innovation Research Group (SIRG), and director of the Technological and Informatics Studies Center (TISC), American University in the Emirates, United Arab Emirates.

This book highlights the latest research on distributed computing and artificial intelligence. DCAI 2021 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 55 papers were submitted to main track and special sessions, by authors from 24 different countries representing a truly “wide area network” of research activity. Moreover, DCAI 2021 Special Sessions have been a very useful tool in order to complement the regular program with new or emerging topics of particular interest to the participating community. The technical program of the Special Sessions of DCAI 2021 has selected 23 papers. We would like to thank all the contributing authors, the members of the Program Committees, the sponsors (IBM, Armundia Group, EurAI, AEPIA, APPIA, CINI, OIT, UGR, HU, SCU, USAL, AIR Institute and UNIVAQ) and the Organizing Committee of the University of Salamanca for their hard and highly valuable work.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems. The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‐centric society of the future. New applications are increasingly reliant on machine‐to‐machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‐optimization for the task at hand while ensuring high dependability and ultra‐low latency. Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‐making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required. AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‐agent systems and network ultra‐broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.