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This book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireless networks domain. Mining Over Air describes the problems and their solutions for wireless network performance and quality, device quality readiness and returns analytics, wireless resource usage profiling, network traffic anomaly detection, intelligence-based self-organizing networks, telecom marketing, social influence, and other important applications in the telecom industry. Written by authors who study big data analytics in wireless networks and telecommunication markets from both industrial and academic perspectives, the book targets the pain points in telecommunication networks and markets through big data. Designed for both practitioners and researchers, the book explores the intersection between the development of new engineering technology and uses data from the industry to understand consumer behavior. It combines engineering savvy with insights about human behavior. Engineers will understand how the data generated from the technology can be used to understand the consumer behavior and social scientists will get a better understanding of the data generation process.
This reference text will benefit readers in enhancing their understanding of the recent technologies, protocols, and challenges in various stages of development of wireless communication and networking. The text discusses the cellular concepts of 4G, 5G, and 6G along with their challenges. It covers topics related to vehicular technology, wherein vehicles communicate with the traffic and the environment around them using short-range wireless signals. The text comprehensively covers important topics including use of the Internet of Things (IoT) in wireless communication, architecture, and protocols. It further covers the role of smart antennas in emerging wireless technologies. The book Discusses advanced techniques used in the field of wireless communication. Covers technologies including network slicing, 5G wireless communication, and TV white space technology. Discusses practical applications including drone delivery systems, public safety, IoT, virtual reality, and smart cities. Covers radio theory and applications for wireless communication with ranges of centimeters to hundreds of meters. Discusses important topics including metamaterials, inductance coupling for loop antennas, bluetooth low energy, wireless security, and wireless sensor networks. Discussing latest technologies including 5G, 6G, IoT, vehicular technology and TV white space technology, this text will be useful for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, and electronics and communication engineering.
This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
This book demonstrates that the reliable and secure communication performance of maritime communications can be significantly improved by using intelligent reflecting surface (IRS) aided communication, privacy-aware Internet of Things (IoT) communications, intelligent resource management and location privacy protection. In the IRS aided maritime communication system, the reflecting elements of IRS can be intelligently controlled to change the phase of signal, and finally enhance the received signal strength of maritime ships (or sensors) or jam maritime eavesdroppers illustrated in this book. The power and spectrum resource in maritime communications can be jointly optimized to guarantee the quality of service (i.e., security and reliability requirements), and reinforcement leaning is adopted to smartly choose the resource allocation strategy. Moreover, learning based privacy-aware offloading and location privacy protection are proposed to intelligently guarantee the privacy-preserving requirements of maritime ships or (sensors). Therefore, these communication schemes based on reinforcement learning algorithms can help maritime communication systems to improve the information security, especially in dynamic and complex maritime environments. This timely book also provides broad coverage of the maritime wireless communication issues, such as reliability, security, resource management, and privacy protection. Reinforcement learning based methods are applied to solve these issues. This book includes four rigorously refereed chapters from prominent international researchers working in this subject area. The material serves as a useful reference for researchers, graduate students. Practitioners seeking solutions to maritime wireless communication and security related issues will benefit from this book as well.
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
The two volume set CCIS 775 and 776 constitutes the refereed proceedings of the First International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2017, held in Kolkata, India, in March 2017. The 90 revised full papers presented in the two volumes were carefully reviewed and selected from 276 submissions. The papers are organized in topical sections on data science and advanced data analytics; signal processing and communications; microelectronics, sensors, intelligent networks; computational forensics (privacy and security); computational intelligence in bio-computing; computational intelligence in mobile and quantum computing; intelligent data mining and data warehousing; computational intelligence.
The book presents selected papers from the International Conference on Data Science and Communication (ICTDsC 2023) organized by the Department of Electronics and Communication Engineering and Department of Engineering Science and Humanities (DESH) Siliguri Institute of Technology, India during 23 – 24 March 2023 in Siliguri, India. The book covers state-of-the-art research insights on artificial intelligence, machine learning, big data, data analytics, cyber security and forensic, network and mobile security, advanced computing, cloud computing, quantum computing, electronics system, Internet of Things, robotics and automations, blockchain and software technology, and digital technologies for future.
The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Analytics and Insights (ICDAI 2023), organized by Techno International, Kolkata, India, during May 11–13, 2023. The book covers important topics like sensor and network data analytics and insights; big data analytics and insights; biological and biomedical data analysis and insights; optimization techniques, time series analysis and forecasting; power and energy systems data analytics and insights; civil and environmental data analytics and insights; and industry and applications.
This book discusses the latest research, theoretical, and experimental research innovations in drone data analytics in aerial computing. Drone data analytics guarantees that the right people have the correct data at their fingertips whenever they need it. The contents also discuss the challenges faced with drone data analytics, such as due to the high mobility of drones, aerial computing is significantly different from terrestrial computing. It also includes case studies from leading drone vendors. The book also focuses on the comparison of data management and security mechanisms in drone data analytics. This book is useful to those working in agriculture, mining, waste management, and defenses department.
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.