Future Communication Systems Using Artificial Intelligence Internet Of Things And Data Science

This book covers topics related to Artificial Intelligence, Internet of Things (IoT), and Data Science for future communications systems. It is beneficial for undergraduate, graduate, postgraduate students, researchers, academicians, institutions, engineers, professionals.

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.

This book focuses mainly on the usages of three key technologies: IoT, big data, and AI for various day to day applications. Further, it explores the possibilities of future research based on the usages of latest information systems. This book explores the current research and challenges to be faced by different researchers for building intelligent information solutions using key technologies; IoT, big data, and AI in improving quality of lives in smart cities and explores the limitations and capabilities of these three key computing technologies. The book is organized into three major parts; each part includes chapters exploring a specific topic, and there are: PART-1: IoT for Real World Solutions , (ii) Part-2: Big Data And Cloud Computing for Innovative Solutions For Day to Day Lives, and (iii) Part-3 Artificial Intelligence for Everyday Lives. This book may be useful to the scientists, scholars, and researchers who are working in the field of computer science and engineering, and communication engineering, along with the students in these subjects who are working or willing to work on IoT, big data, and AI technologies for improving quality of everyday life. Specialists as well as student readers find the book chapters encouraging and helpful. IoT, data science & cloud, and AI all are the undergraduate (UG/ bachelor) subjects. Use of these three key technologies for building new applications for better world is helpful for UG and postgraduate (PG/ MS) Programmes students (as an elective and core course). This book may also be very useful for the Ph.D. (research scholars) during their course work and may be used as an instrument to identify the different challenges associated with information systems.

This reference text discusses advances in wireless communication, design challenges, and future research directions to design reliable wireless communication. The text discusses emerging technologies including wireless sensor networks, Internet of Things (IoT), cloud computing, mm-Wave, Massive MIMO, cognitive radios (CR), visible light communication (VLC), wireless optical communication, signal processing, and channel modeling. The text covers artificial intelligence-based applications in wireless communication, machine learning techniques and challenges in wireless sensor networks, and deep learning for channel and bandwidth estimation during optical wireless communication. The text will be useful for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, and electronics and communication engineering.

This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.

THE NEW ADVANCED SOCIETY Included in this book are the fundamentals of Society 5.0, artificial intelligence, and the industrial Internet of Things, featuring their working principles and application in different sectors. A 360-degree view of the different dimensions of the digital revolution is presented in this book, including the various industries transforming industrial manufacturing, the security and challenges ahead, and the far-reaching implications for society and the economy. The main objective of this edited book is to cover the impact that the new advanced society has on several platforms such as smart manufacturing systems, where artificial intelligence can be integrated with existing systems to make them smart, new business models and strategies, where anything and everything is possible through the internet and cloud, smart food chain systems, where food products can be delivered to any corner of the world at any time and in any situation, smart transport systems in which robots and self-driven cars are taking the lead, advances in security systems to assure people of their privacy and safety, and smart healthcare systems, where biochips can be incorporated into the human body to predict deadly diseases at early stages. Finally, it can be understood that the social reformation of Society 5.0 will lead to a society where every person leads an active and healthy life. Audience The targeted audience for this book includes research scholars and industry engineers in artificial intelligence and information technology, engineering students, cybersecurity experts, government research agencies and policymakers, business leaders, and entrepreneurs. Sandeep Kumar Panda, PhD is an associate professor in the Department of Data Science and Artificial Intelligence at IcfaiTech (Faculty of Science and Technology), ICFAI Foundation for Higher Education, Hyderabad. His research areas include artificial intelligence, IoT, blockchain technology, cloud computing, cryptography, computational intelligence, and software engineering. Ramesh Kumar Mohapatra, PhD is an assistant professor in the Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India. His research interests include optical character recognition, document image analysis, video processing, secure computing, and machine learning. Subhrakanta Panda, PhD is an assistant professor in the Department of Computer Science and Information Systems, BITS-PILANI, Hyderabad Campus, Jawahar Nagar, Hyderabad, India. His research interests include social network analysis, cloud computing, security testing, and blockchain. S. Balamurugan, PhD is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.