This text provides novel smart network systems, wireless telecommunications infrastructures, and computing capabilities to help healthcare systems using computing techniques like IoT, cloud computing, machine and deep learning Big Data along with smart wireless networks. It discusses important topics, including robotics manipulation and analysis in smart healthcare industries, smart telemedicine framework using machine learning and deep learning, role of UAV and drones in smart hospitals, virtual reality based on 5G/6G and augmented reality in healthcare systems, data privacy and security, nanomedicine, and cloud-based artificial intelligence in healthcare systems. The book: * Discusses intelligent computing through IoT and Big Data in secure and smart healthcare systems. * Covers algorithms, including deterministic algorithms, randomized algorithms, iterative algorithms, and recursive algorithms. * Discusses remote sensing devices in hospitals and local health facilities for patient evaluation and care. * Covers wearable technology applications such as weight control and physical activity tracking for disease prevention and smart healthcare. This book will be useful for senior undergraduate, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and information technology. Discussing concepts of smart networks, advanced wireless communication, and technologies in setting up smart healthcare services, this text will be useful for senior undergraduate, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and information technology. It covers internet of things (IoT) implementation and challenges in healthcare industries, wireless network, and communication-based optimization algorithms for smart healthcare devices.

This book discusses the recent advanced technologies in Intelligent Transportation Systems (ITS), with a view on how Unmanned Aerial Vehicles (UAVs) cooperate with future vehicles. ITS technologies aim to achieve traffic efficiency and advance transportation safety and mobility. Known as aircrafts without onboard human operators, UAVs are used across the world for civilian, commercial, as well as military applications. Common deployment include policing and surveillance, product deliveries, aerial photography, agriculture, and drone racing. As the air-ground cooperation enables more diverse usage, this book addresses the holistic aspects of the recent advanced technologies in ITS, including Information and Communication Technologies (ICT), cyber security, and service management from principle and engineering practice aspects. This is achieved by providing in-depth study on several major topics in the fields of telecommunications, transport services, cyber security, and so on. The book will serve as a useful text for transportation, energy, and ICT societies from both academia and industrial sectors. Its broad scope of introductory knowledge, technical reviews, discussions, and technology advances will also benefit potential authors.

Wireless network security research is multidisciplinary in nature, including data analysis, economics, mathematics, forensics, information technology, and computer science. This text covers cutting-edge research in computational intelligence systems from diverse fields on the complex subject of wireless communication security. It discusses important topics including computational intelligence in wireless network and communications, artificial intelligence and wireless communication security, security risk scenarios in communications, security/resilience metrics and their measurements, data analytics of cyber-crimes, modeling of wireless communication security risks, advances in cyber threats and computer crimes, adaptive and learning techniques for secure estimation and control, decision support systems, fault tolerance and diagnosis, cloud forensics and information systems, and intelligent information retrieval. The book: Discusses computational algorithms for system modeling and optimization in security perspective Focuses on error prediction and fault diagnosis through intelligent information retrieval via wireless technologies Explores a group of practical research problems where security experts can help develop new data-driven methodologies Covers application on artificial intelligence and wireless communication security risk perspective The text is primarily written for senior undergraduate, graduate students, and researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering. The text comprehensively discusses wide range of wireless communication techniques with emerging computational intelligent trends, to help readers understand the role of wireless technologies in applications touching various spheres of human life with the help of hesitant fuzzy sets based computational modeling. It will be a valuable resource for senior undergraduate, graduate students, and researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

This book (CCIS 899) constitutes the refereed proceedings of the First International Conference on Applications of Computing and Communication Technologies, ICACCT 2018, held in Delhi, India, in March 2018. The 30 full papers were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on communication and system technologies, computing and network technologies, application and services.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation.

Vehicular traffic congestion and accidents remain universal issues in today's world. Due to the continued growth in the use of vehicles, optimizing traffic management operations is an immense challenge. To reduce the number of traffic accidents, improve the performance of transportation systems, enhance road safety, and protect the environment, vehicular ad-hoc networks have been introduced. Current developments in wireless communication, computing paradigms, big data, and cloud computing enable the enhancement of these networks, equipped with wireless communication capabilities and high-performance processing tools. Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks is a pivotal reference source that provides vital research on cloud and data analytic applications in intelligent transportation systems. While highlighting topics such as location routing, accident detection, and data warehousing, this publication addresses future challenges in vehicular ad-hoc networks and presents viable solutions. This book is ideally designed for researchers, computer scientists, engineers, automobile industry professionals, IT practitioners, academicians, and students seeking current research on cloud computing models in vehicular networks.

The optimization of traffic management operations has become a considerable challenge in today's global scope due to the significant increase in the number of vehicles, traffic congestions, and automobile accidents. Fortunately, there has been substantial progress in the application of intelligent computing devices to transportation processes. Vehicular ad-hoc networks (VANETs) are a specific practice that merges the connectivity of wireless technologies with smart vehicles. Despite its relevance, empirical research is lacking on the developments being made in VANETs and how certain intelligent technologies are being applied within transportation systems. IoT and Cloud Computing Advancements in Vehicular Ad-Hoc Networks provides emerging research exploring the theoretical and practical aspects of intelligent transportation systems and analyzing the modern techniques that are being applied to smart vehicles through cloud technology. Featuring coverage on a broad range of topics such as health monitoring, node localization, and fault tolerance, this book is ideally designed for network designers, developers, analysists, IT specialists, computing professionals, researchers, academics, and post-graduate students seeking current research on emerging computing concepts and developments in vehicular ad-hoc networks.

Vehicular traffic congestion and accidents remain universal issues in today's world. Due to the continued growth in the use of vehicles, optimizing traffic management operations is an immense challenge. To reduce the number of traffic accidents, improve the performance of transportation systems, enhance road safety, and protect the environment, vehicular ad-hoc networks have been introduced. Current developments in wireless communication, computing paradigms, big data, and cloud computing enable the enhancement of these networks, equipped with wireless communication capabilities and high-performance processing tools. Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks is a pivotal reference source that provides vital research on cloud and data analytic applications in intelligent transportation systems. While highlighting topics such as location routing, accident detection, and data warehousing, this publication addresses future challenges in vehicular ad-hoc networks and presents viable solutions. This book is ideally designed for researchers, computer scientists, engineers, automobile industry professionals, IT practitioners, academicians, and students seeking current research on cloud computing models in vehicular networks.

The optimization of traffic management operations has become a considerable challenge in today's global scope due to the significant increase in the number of vehicles, traffic congestions, and automobile accidents. Fortunately, there has been substantial progress in the application of intelligent computing devices to transportation processes. Vehicular ad-hoc networks (VANETs) are a specific practice that merges the connectivity of wireless technologies with smart vehicles. Despite its relevance, empirical research is lacking on the developments being made in VANETs and how certain intelligent technologies are being applied within transportation systems. IoT and Cloud Computing Advancements in Vehicular Ad-Hoc Networks provides emerging research exploring the theoretical and practical aspects of intelligent transportation systems and analyzing the modern techniques that are being applied to smart vehicles through cloud technology. Featuring coverage on a broad range of topics such as health monitoring, node localization, and fault tolerance, this book is ideally designed for network designers, developers, analysists, IT specialists, computing professionals, researchers, academics, and post-graduate students seeking current research on emerging computing concepts and developments in vehicular ad-hoc networks.