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Convergence Of Deep Learning And Internet Of Things Computing And Technology
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Book Synopsis Convergence of Deep Learning and Internet of Things: Computing and Technology by : Kavitha, T.
Download or read book Convergence of Deep Learning and Internet of Things: Computing and Technology written by Kavitha, T. and published by IGI Global. This book was released on 2022-12-19 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.
Book Synopsis Convergence of Deep Learning and Artificial Intelligence in Internet of Things by : Ajay Rana
Download or read book Convergence of Deep Learning and Artificial Intelligence in Internet of Things written by Ajay Rana and published by CRC Press. This book was released on 2022-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. • Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things. • Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe. • Explores the importance of blockchain technology in the Internet of Things security issues. • Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy. • Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications. This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It further discusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.
Book Synopsis Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing by : Velayutham, Sathiyamoorthi
Download or read book Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing written by Velayutham, Sathiyamoorthi and published by IGI Global. This book was released on 2021-01-29 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues.
Book Synopsis Convergence of Deep Learning in Cyber-IoT Systems and Security by : Rajdeep Chakraborty
Download or read book Convergence of Deep Learning in Cyber-IoT Systems and Security written by Rajdeep Chakraborty and published by John Wiley & Sons. This book was released on 2022-12-08 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: CONVERGENCE OF DEEP LEARNING IN CYBER-IOT SYSTEMS AND SECURITY In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through deep learning techniques and analytics with the study of all these systems. This book provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, as well as the exposed security issues in these systems. The 20 chapters are organized into four parts. Part I gives the various approaches that have evolved from machine learning to deep learning. Part II presents many innovative solutions, algorithms, models, and implementations based on deep learning. Part III covers security and safety aspects with deep learning. Part IV details cyber-physical systems as well as a discussion on the security and threats in cyber-physical systems with probable solutions. Audience Researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity and cryptography.
Author :Parikshit N. Mahalle, Gitanjali R. Shinde, Prachi M. Joshi Publisher :Bentham Science Publishers ISBN 13 :9815179195 Total Pages :196 pages Book Rating :4.8/5 (151 download)
Book Synopsis Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications by : Parikshit N. Mahalle, Gitanjali R. Shinde, Prachi M. Joshi
Download or read book Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications written by Parikshit N. Mahalle, Gitanjali R. Shinde, Prachi M. Joshi and published by Bentham Science Publishers. This book was released on 2023-12-25 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume showcases upcoming trends and applications that are set to redefine our technological landscape. Chapters comprise referenced reviews focused on the recent research that introduces new methods and techniques for using AI in Industry 4.0, and the integration of Internet of Things (IoT) to drive new industrial processes. The contributors have discussed challenges in industry 4.0 along with the applications and the way it is shaping different industries. Key themes: AI in Communication Media: Uncover the latest research, with insights into the challenges and adoption of AI in remote processes. New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing. IoT and AI for Smart Systems: Understand IoT with a special focus on enhancing smart systems, in different industries, including agriculture and transaction processing Explorable AI: Gain a quick understanding of Explainable AI (XAI) and its role in improving the predictability and transparency of IoT applications. Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, big data, and cloud computing.
Book Synopsis Convergence of Blockchain, AI, and IoT by : R. Indrakumari
Download or read book Convergence of Blockchain, AI, and IoT written by R. Indrakumari and published by CRC Press. This book was released on 2021-12-23 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convergence of Blockchain, AI, and IoT: Concepts and Challenges discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy. The book provides an overview of the clinical scientific research enabling smart diagnosis equipment through AI. It presents the role these technologies play in augmented reality and blockchain, covers digital currency managed with bitcoin, and discusses deep learning and how it can enhance human thoughts and behaviors. Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.
Download or read book Edge AI written by Xiaofei Wang and published by Springer Nature. This book was released on 2020-08-31 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.
Book Synopsis The Convergence of Internet of Things and Cloud for Smart Computing by : Parikshit N. Mahalle
Download or read book The Convergence of Internet of Things and Cloud for Smart Computing written by Parikshit N. Mahalle and published by CRC Press. This book was released on 2021-08-03 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the know-how of the real-time IoT application development activity including a basic understanding of the IoT architecture, use cases, smart computing, and the associated challenges in design and development of the IoT system. All the technical details related to protocol stack, technologies, and platforms used for the implementation are explained. It further includes techniques and case studies that include smart computing on the IoT–Cloud models along with test beds for experimentation purposes. The book aims at setting up the groundwork for the creation of applications that can help make day-to-day tasks simpler by meeting the needs of varied sectors like education, health care, agriculture, and so forth. Features: • Covers IoT cloud convergence with a focus on complex industrial IoT case studies. • Discusses the broad background of IoT–Cloud convergence architectures and its fundamentals along with resource provisioning mechanisms. • Emphasizes the use of context in developing context-aware IoT solutions. • Presents a novel C-model that explains the IoT application development phases. • Discusses a simplified convergence model that depicts the role of Cloud in an IoT application. This book aims at graduate students, researchers, and professionals getting started in the IoT field.
Book Synopsis Deep Learning: Convergence to Big Data Analytics by : Murad Khan
Download or read book Deep Learning: Convergence to Big Data Analytics written by Murad Khan and published by Springer. This book was released on 2018-12-30 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.
Book Synopsis Deep Learning for Internet of Things Infrastructure by : Uttam Ghosh
Download or read book Deep Learning for Internet of Things Infrastructure written by Uttam Ghosh and published by CRC Press. This book was released on 2021-09-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.
Book Synopsis Edge Intelligence in the Making by : Sen Lin
Download or read book Edge Intelligence in the Making written by Sen Lin and published by Springer Nature. This book was released on 2022-06-01 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data. Indeed, the marriage of edge computing and AI has resulted in innovative solutions, namely edge intelligence or edge AI. Nevertheless, research and practice on this emerging inter-disciplinary field is still in its infancy stage. To facilitate the dissemination of the recent advances in edge intelligence in both academia and industry, this book conducts a comprehensive and detailed survey of the recent research efforts and also showcases the authors' own research progress on edge intelligence. Specifically, the book first reviews the background and present motivation for AI running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence. This emerging interdisciplinary field offers many open problems and yet also tremendous opportunities, and this book only touches the tip of iceberg. Hopefully, this book will elicit escalating attention, stimulate fruitful discussions, and open new directions on edge intelligence.
Book Synopsis Artificial Intelligence and IoT by : Kalaiselvi Geetha Manoharan
Download or read book Artificial Intelligence and IoT written by Kalaiselvi Geetha Manoharan and published by Springer Nature. This book was released on 2021-02-12 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors’ intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors’ attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.
Book Synopsis The Fusion of Internet of Things, Artificial Intelligence, and Cloud Computing in Health Care by : Patrick Siarry
Download or read book The Fusion of Internet of Things, Artificial Intelligence, and Cloud Computing in Health Care written by Patrick Siarry and published by Springer Nature. This book was released on 2021-08-11 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the convergence technologies like cloud computing, artificial intelligence (AI) and Internet of Things (IoT) in healthcare and how they can help all stakeholders in the healthcare sector. The book is a proficient guide on the relationship between AI, IoT and healthcare and gives examples into how IoT is changing all aspects of the healthcare industry. Topics include remote patient monitoring, the telemedicine ecosystem, pattern imaging analytics using AI, disease identification and diagnosis using AI, robotic surgery, prediction of epidemic outbreaks, and more. The contributors include applications and case studies across all areas of computational intelligence in healthcare data. The authors also include workflow in IoT-enabled healthcare technologies and explore privacy and security issues in healthcare-based IoT.
Book Synopsis Convergence Of Artificial Intelligence And Blockchain Technologies, The: Challenges And Opportunities by : Sam Goundar
Download or read book Convergence Of Artificial Intelligence And Blockchain Technologies, The: Challenges And Opportunities written by Sam Goundar and published by World Scientific. This book was released on 2022-05-18 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the growing convergence between Blockchain and Artificial Intelligence for Big Data, Multi-Agent systems, the Internet of Things and 5G technologies. Using real case studies and project outcomes, it illustrates the intricate details of blockchain in these real-life scenarios. The contributions from this volume bring a state-of-the-art assessment of these rapidly evolving trends in a creative way and provide a key resource for all those involved in the study and practice of AI and Blockchain.
Book Synopsis Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by : Raut, Roshani
Download or read book Examining the Impact of Deep Learning and IoT on Multi-Industry Applications written by Raut, Roshani and published by IGI Global. This book was released on 2021-01-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
Book Synopsis Cloud-IoT Technologies in Society 5.0 by : Kamta Nath Mishra Ph.D.
Download or read book Cloud-IoT Technologies in Society 5.0 written by Kamta Nath Mishra Ph.D. and published by Springer Nature. This book was released on 2023-05-11 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides in-depth knowledge in the areas of convergence of cloud-IoT technologies and industry 4.0 with society 5.0, machine-to-machine communication, machine-to-person communication, techno-psychological perspective of society 5.0, sentiment analysis of smart digital societies, multi-access edge computing for 5G networks, discovery & location reporting of multi-access edge enabled clients/servers, m-health systems, enhancing the concert of M-health technologies in smart societies, supervising communication services in smart societies, life quality enhancement in smart city societies, multiple disease infection predictions, and societal opinion mining algorithms for smart cities societies using cloud-IoT integrated intelligent machine / deep learning technologies to the readers in the distributive environment. In this book, the authors have mandatorily discussed the implementation of cloud-IoT based machine learning technologies like clustering technique, Naïve Bayes classifier, artificial neural network (ANN), Firefly algorithm, Rough set classifiers, support vector machine classifier, decision tree classifier, ensemble classifier, random forest, and deep learning algorithms to analyze the behavior of intelligent machines and human habits using automated data scheduling and smart digital networks. At present, we live in a self-motivated and dynamic global society where technologies and challenges are unexpectedly changing overnight. These rapid changes in globalization and technological advances are creating new market forces every day. Therefore, day-to-day innovation is essential for any business or institution to survive and flourish in such an atmosphere. Though, innovation is no longer just to create value to do good to individuals, societies, or organizations. The utmost purpose of innovation is to create a smart futuristic society where people can enjoy the best quality of life using natural resources and manmade technologies including cloud-IoT technologies, and industry 4.0. Hence, the innovators and their innovations must search for intelligent solutions to tackle major socio-technical problems and remove barriers of rural, urban and smart city societies. The smart digitization and intelligent implementation of manufacturing development processes are the necessities for today’s rural, urban, and smart city industries. All types of industries including development, manufacturing, and research are presently shifting from bunch production to customized production. The fast advancements in manufacturing technologies have an in-depth impact on all types of societies including societies of rural areas, urban areas, and smart cities. Industry 4.0 includes the Internet of Things (IoT), Industrial Internet, Smart Manufacturing, Cloud-based computing, and Manufacturing Technologies. The objective of this book is to establish linkage between the Industry 4.0 components and various rural, urban & smart city societies (including society 5.0) to bring actual prosperity where human values, peace of mind, human relations, man-machine-relations, and calmness will have utmost preference. These objectives can be achieved by the integration of human societal values, and social opinion mining (SOM) approaches with the existing technologies.
Book Synopsis Intelligent Internet of Things Networks by : Haipeng Yao
Download or read book Intelligent Internet of Things Networks written by Haipeng Yao and published by Springer Nature. This book was released on 2023-06-09 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the Internet of Things Network and Machine Learning and introduces Internet of Things architecture. It designs a new intelligent IoT network architecture and introduces different machine learning approaches to investigate solutions. It discusses how machine learning can help network awareness and achieve network intelligent control. It also dicusses the emerging network techniques that can enable the development of intelligent IoT networks. This book applies several intelligent approaches for efficient resource scheduling in networks. It discusses Mobile Edge Computing aided intelligent IoT and focuses mainly on the resource sharing and edge computation offloading problems in mobile edge networks. The blockchain-based IoT (which allows fairly and securely renting resources and establishing contracts) is discussed as well. The Internet of Things refers to the billions of physical devices that are now connected to and transfer data through the Internet without requiring human-to-human or human-to-computer interaction. According to Gartner's prediction, there will be more than 37 billion IoT connections in the future year of 2025. However, with large-scale IoT deployments, IoT networks are facing challenges in the aspects of scalability, privacy, and security. The ever-increasing complexity of the IoT makes effective monitoring, overall control, optimization, and auditing of the network difficult. Recently, artificial intelligence (AI) and machine learning (ML) approaches have emerged as a viable solution to address this challenge. Machine learning can automatically learn and optimize strategy directly from experience without following pre-defined rules. Therefore, it is promising to apply machine learning in IoT network control and management to leverage powerful machine learning adaptive abilities for higher network performance. This book targets researchers working in the Internet of Things networks as well as graduate students and undergraduate students focused on this field. Industry managers, and government research agencies in the fields of the IoT networks will also want to purchase this book.
