Tinyml For Edge Intelligence In Iot And Lpwan Networks

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TinyML for Edge Intelligence in IoT and LPWAN Networks

Author : Bharat S Chaudhari
Publisher : Elsevier
ISBN 13 : 0443222037
Total Pages : 520 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis TinyML for Edge Intelligence in IoT and LPWAN Networks by : Bharat S Chaudhari

Download or read book TinyML for Edge Intelligence in IoT and LPWAN Networks written by Bharat S Chaudhari and published by Elsevier. This book was released on 2024-06-17 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to IoT and LPWANs. It starts by providing the foundations of IoT/LPWANs, low power embedded systems and hardware, the role of artificial intelligence and machine learning in communication networks in general and cloud/edge intelligence. It then presents the concepts, methods, algorithms and tools of TinyML. Practical applications of the use of TinyML are given from health and industrial fields which provide practical guidance on the design of applications and the selection of appropriate technologies. TinyML for Edge Intelligence in IoT and LPWAN Networks is highly suitable for academic researchers and professional system engineers, architects, designers, testers, deployment engineers seeking to design ultra-lower power and time-critical applications. It would also help in designing the networks for emerging and future applications for resource-constrained nodes. This book provides one-stop solutions for emerging TinyML for IoT and LPWAN applications. The principles and methods of TinyML are explained, with a focus on how it can be used for IoT, LPWANs, and 5G applications. Applications from the healthcare and industrial sectors are presented. Guidance on the design of applications and the selection of appropriate technologies is provided.

IoT Edge Intelligence

Author : Souvik Pal
Publisher : Springer Nature
ISBN 13 : 3031583884
Total Pages : 392 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis IoT Edge Intelligence by : Souvik Pal

Download or read book IoT Edge Intelligence written by Souvik Pal and published by Springer Nature. This book was released on with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Shaping the Future of IoT with Edge Intelligence

Author : Rute C. Sofia
Publisher : CRC Press
ISBN 13 : 100381218X
Total Pages : 376 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Shaping the Future of IoT with Edge Intelligence by : Rute C. Sofia

Download or read book Shaping the Future of IoT with Edge Intelligence written by Rute C. Sofia and published by CRC Press. This book was released on 2024-01-08 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the technologies that empower edge intelligence, along with their use in novel IoT solutions. Specifically, it presents how 5G/6G, Edge AI, and Blockchain solutions enable novel IoT-based decentralized intelligence use cases at the edge of the cloud/edge/IoT continuum. Emphasis is placed on presenting how these technologies support a wide array of functional and non-functional requirements spanning latency, performance, cybersecurity, data protection, real-time performance, energy efficiency, and more. The various chapters of the book are contributed by several EU-funded projects, which have recently developed novel IoT platforms that enable the development and deployment of edge intelligence applications based on the cloud/edge paradigm. Each one of the projects employs its own approach and uses a different mix of networking, middleware, and IoT technologies. Therefore, each of the chapters of the book contributes a unique perspective on the capabilities of enabling technologies and their integration in practical real-life applications in different sectors. The book is structured in five distinct parts. Each one of the first four parts focuses on a specific set of enabling technologies for edge intelligence and smart IoT applications in the cloud/edge/IoT continuum. Furthermore, the fifth part provides information about complementary aspects of next-generation IoT technology, including information about business models and IoT skills. Specifically: The first part focuses on 5G/6G networking technologies and their roles in implementing edge intelligence applications. The second part presents IoT applications that employ machine learning and other forms of Artificial Intelligence at the edge of the network. The third part illustrates decentralized IoT applications based on distributed ledger technologies. The fourth part is devoted to the presentation of novel IoT applications and use cases spanning the cloud/edge/IoT continuum. The fifth part discusses complementary aspects of IoT technologies, including business models and digital skills.

Intelligent Internet of Things Networks

Author : Haipeng Yao
Publisher : Springer Nature
ISBN 13 : 303126987X
Total Pages : 413 pages
Book Rating : 4.0/5 (312 download)

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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.

LPWAN Technologies for IoT and M2M Applications

Author : Bharat S. Chaudhari
Publisher : Academic Press
ISBN 13 : 0128188812
Total Pages : 456 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis LPWAN Technologies for IoT and M2M Applications by : Bharat S. Chaudhari

Download or read book LPWAN Technologies for IoT and M2M Applications written by Bharat S. Chaudhari and published by Academic Press. This book was released on 2020-03-17 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Low power wide area network (LPWAN) is a promising solution for long range and low power Internet of Things (IoT) and machine to machine (M2M) communication applications. The LPWANs are resource-constrained networks and have critical requirements for long battery life, extended coverage, high scalability, and low device and deployment costs. There are several design and deployment challenges such as media access control, spectrum management, link optimization and adaptability, energy harvesting, duty cycle restrictions, coexistence and interference, interoperability and heterogeneity, security and privacy, and others. LPWAN Technologies for IoT and M2M Applications is intended to provide a one-stop solution for study of LPWAN technologies as it covers a broad range of topics and multidisciplinary aspects of LPWAN and IoT. Primarily, the book focuses on design requirements and constraints, channel access, spectrum management, coexistence and interference issues, energy efficiency, technology candidates, use cases of different applications in smart city, healthcare, and transportation systems, security issues, hardware/software platforms, challenges, and future directions. One stop guide to the technical details of various low power long range technologies such as LoRaWAN, Sigfox, NB-IoT, LTE-M and others Describes the design aspects, network architectures, security issues and challenges Discusses the performance, interference, coexistence issues and energy optimization techniques Includes LPWAN based intelligent applications in diverse areas such as smart city, traffic management, health and others Presents the different hardware and software platforms for LPWANs Provides guidance on selecting the right technology for an application

Heterogenous Computational Intelligence in Internet of Things

Author : Pawan Singh
Publisher : CRC Press
ISBN 13 : 1000967948
Total Pages : 376 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Heterogenous Computational Intelligence in Internet of Things by : Pawan Singh

Download or read book Heterogenous Computational Intelligence in Internet of Things written by Pawan Singh and published by CRC Press. This book was released on 2023-10-23 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have seen a sharp increase in the development of data transfer techniques in the networking industry over the past few years. We can see that the photos are assisting clinicians in detecting infection in patients even in the current COVID-19 pandemic condition. With the aid of ML/AI, medical imaging, such as lung X-rays for COVID-19 infection, is crucial in the early detection of many diseases. We also learned that in the COVID-19 scenario, both wired and wireless networking are improved for data transfer but have network congestion. An intriguing concept that has the ability to reduce spectrum congestion and continuously offer new network services is providing wireless network virtualization. The degree of virtualization and resource sharing varies between the paradigms. Each paradigm has both technical and non-technical issues that need to be handled before wireless virtualization becomes a common technology. For wireless network virtualization to be successful, these issues need careful design and evaluation. Future wireless network architecture must adhere to a number of Quality of Service (QoS) requirements. Virtualization has been extended to wireless networks as well as conventional ones. By enabling multi-tenancy and tailored services with a wider range of carrier frequencies, it improves efficiency and utilization. In the IoT environment, wireless users are heterogeneous, and the network state is dynamic, making network control problems extremely difficult to solve as dimensionality and computational complexity keep rising quickly. Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based management on the QoS required by each Software Defined Network (SDN) service. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective.

Federated Learning for IoT Applications

Author : Satya Prakash Yadav
Publisher : Springer Nature
ISBN 13 : 3030855597
Total Pages : 269 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Federated Learning for IoT Applications by : Satya Prakash Yadav

Download or read book Federated Learning for IoT Applications written by Satya Prakash Yadav and published by Springer Nature. This book was released on 2022-02-02 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users’ privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federated learning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.

Edge Computational Intelligence for AI-Enabled IoT Systems

Author : Shrikaant Kulkarni
Publisher : CRC Press
ISBN 13 : 1003825125
Total Pages : 347 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Edge Computational Intelligence for AI-Enabled IoT Systems by : Shrikaant Kulkarni

Download or read book Edge Computational Intelligence for AI-Enabled IoT Systems written by Shrikaant Kulkarni and published by CRC Press. This book was released on 2024-02-26 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs and resilience from network failure, and the book explains the advantages of systems and applications using intelligent IoT devices that are at the edge of a network and close to users. It explains how to make most of edge and cloud computing as complementary technologies or used in isolation for extensive and widespread applications. The advancement in IoT devices, networking facilities, parallel computation and 5G, and robust infrastructure for generalized machine learning have made it possible to employ edge computational intelligence in diverse areas and in diverse ways. The book begins with chapters that cover Edge AI services on offer as compared to conventional systems. These are followed by chapters that discuss security and privacy issues encountered during the implementation and execution of edge AI and computing services The book concludes with chapters looking at applications spread across different areas of edge AI and edge computing and also at the role of computational intelligence in AI-driven IoT systems.

Low-Power Wide Area Networks for Large Scale Iot

Author :
Publisher : CRC Press
ISBN 13 : 9781003426974
Total Pages : 0 pages
Book Rating : 4.4/5 (269 download)

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Book Synopsis Low-Power Wide Area Networks for Large Scale Iot by :

Download or read book Low-Power Wide Area Networks for Large Scale Iot written by and published by CRC Press. This book was released on 2024-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents a comprehensive exploration of LPWANs, delving into their fundamental concepts, underlying technologies, and the multifaceted challenges they tackle. This book recognizes that LPWANs don't operate in isolation; they are intimately intertwined with Artificial Intelligence and Machine Learning (AI/ML) technologies, which play a pivotal role in optimizing LPWAN performance and capabilities. The book is a collection of original contributions regarding air interface, transmission technologies and novel network architectures, such as network slicing, cloud/fog/edge computing, ad hoc networks and software defined network. Also, this book provides a guide for researchers of IoT applications to choose the suitable LPWAN technologies and describe the design aspects, network architectures, security issues and challenges. This book: Explains machine learning algorithms onto low-power wide area network sensors for compressed communications. Illustrates wireless-based internet of things networks using low-power wide area networks technology for quality air. Presents cognitive internet of things networks using wireless communication, and low power wide area network technologies for Ad Hoc Networks. Discusses a comprehensive study of low-power wide area networks for flying Ad Hoc networks. Showcases the study of energy efficient techniques aided by low-power wide area network technologies for the internet of things networks. This book is primarily written for senior undergraduate, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology"--

Real-Time Intelligence for Heterogeneous Networks

Author : Fadi Al-Turjman
Publisher : Springer Nature
ISBN 13 : 3030756149
Total Pages : 180 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Real-Time Intelligence for Heterogeneous Networks by : Fadi Al-Turjman

Download or read book Real-Time Intelligence for Heterogeneous Networks written by Fadi Al-Turjman and published by Springer Nature. This book was released on 2021-09-02 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses several exciting research topics and applications in the intelligent Heterogenous Networks (Het-Net) and Internet of Things (IoT) era. We are resolving significant issues towards realizing the future vision of the Artificial Intelligence (AI) in IoT-enabled spaces. Such AI-powered IoT solutions will be employed in satisfying critical conditions towards further advances in our daily smart life. This book overviews the associated issues and proposes the most up to date alternatives. The objective is to pave the way for AI-powered IoT-enabled spaces in the next generation Het-Net technologies and open the door for further innovations. The book presents the latest advances and research into heterogeneous networks in critical IoT applications. It discusses the most important problems, challenges, and issues that arise when designing real-time intelligent heterogeneous networks for diverse scenarios.

Learning Techniques for the Internet of Things

Author : Praveen Kumar Donta
Publisher : Springer Nature
ISBN 13 : 303150514X
Total Pages : 334 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Learning Techniques for the Internet of Things by : Praveen Kumar Donta

Download or read book Learning Techniques for the Internet of Things written by Praveen Kumar Donta and published by Springer Nature. This book was released on with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Network Optimization in Intelligent Internet of Things Applications

Author : Payal Khurana Batra
Publisher : CRC Press
ISBN 13 : 1040118771
Total Pages : 349 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Network Optimization in Intelligent Internet of Things Applications by : Payal Khurana Batra

Download or read book Network Optimization in Intelligent Internet of Things Applications written by Payal Khurana Batra and published by CRC Press. This book was released on 2024-09-25 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network Optimization in Intelligent Internet of Things Applications: Principles and Challenges sheds light on the optimization methods that form the basis of effective communication between networked devices. It is an excellent resource as it provides readers with a thorough understanding of the methods, ideas, and tactics essential to attaining seamless connectivity and improving performance. This book presents the fundamental ideas that govern network optimization, from maximizing throughput and lowering latency to handling a variety of communication protocols and minimizing energy use. It also addresses scalability issues, security flaws, and constantly changing IoT environments along with optimization techniques. This book uses cutting-edge research and real-world examples to give readers the knowledge and skills to address the complex problems associated with network optimization in intelligent IoT applications. It also examines machine learning-driven predictive analytics, robust security protocols, flexible routing algorithms, and the integration of edge computing - all crucial instruments for overcoming obstacles and attaining peak performance. This book provides a comprehensive understanding of the principles, challenges, and cutting-edge solutions in IoT network optimization for all kinds of readers, whether it is students, academicians, researchers, or industry professionals. This book unleashes the potential of networked smart devices, which can be unleashed in various sectors.

Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications

Author : Deepak Gupta
Publisher : John Wiley & Sons
ISBN 13 : 1119670071
Total Pages : 464 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications by : Deepak Gupta

Download or read book Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications written by Deepak Gupta and published by John Wiley & Sons. This book was released on 2021-01-07 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to the design, implementation, evaluation, and deployment of emerging technologies for intelligent IoT applications With the rapid development in artificially intelligent and hybrid technologies, IoT, edge, fog-driven, and pervasive computing techniques are becoming important parts of our daily lives. This book focuses on recent advances, roles, and benefits of these technologies, describing the latest intelligent systems from a practical point of view. Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications is also valuable for engineers and professionals trying to solve practical, economic, or technical problems. With a uniquely practical approach spanning multiple fields of interest, contributors cover theory, applications, and design methodologies for intelligent systems. These technologies are rapidly transforming engineering, industry, and agriculture by enabling real-time processing of data via computational, resource-oriented metaheuristics and machine learning algorithms. As edge/fog computing and associated technologies are implemented far and wide, we are now able to solve previously intractable problems. With chapters contributed by experts in the field, this book: Describes Machine Learning frameworks and algorithms for edge, fog, and pervasive computing Considers probabilistic storage systems and proven optimization techniques for intelligent IoT Covers 5G edge network slicing and virtual network systems that utilize new networking capacity Explores resource provisioning and bandwidth allocation for edge, fog, and pervasive mobile applications Presents emerging applications of intelligent IoT, including smart farming, factory automation, marketing automation, medical diagnosis, and more Researchers, graduate students, and practitioners working in the intelligent systems domain will appreciate this book’s practical orientation and comprehensive coverage. Intelligent IoT is revolutionizing every industry and field today, and Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications provides the background, orientation, and inspiration needed to begin.

Connectivity and Edge Computing in IoT: Customized Designs and AI-based Solutions

Author : Jie Gao
Publisher : Springer
ISBN 13 : 9783030887452
Total Pages : 0 pages
Book Rating : 4.8/5 (874 download)

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Book Synopsis Connectivity and Edge Computing in IoT: Customized Designs and AI-based Solutions by : Jie Gao

Download or read book Connectivity and Edge Computing in IoT: Customized Designs and AI-based Solutions written by Jie Gao and published by Springer. This book was released on 2022-11-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers connectivity and edge computing solutions for representative Internet of Things (IoT) use cases, including industrial IoT, rural IoT, Internet of Vehicles (IoV), and mobile virtual reality (VR). Based on their unique characteristics and requirements, customized solutions are designed with targets such as supporting massive connections or seamless mobility and achieving low latency or high energy efficiency. Meanwhile, the book highlights the role of artificial intelligence (AI) in future IoT networks and showcases AI-based connectivity and edge computing solutions. The solutions presented in this book serve the overall purpose of facilitating an increasingly connected and intelligent world. The potential benefits of the solutions include increased productivity in factories, improved connectivity in rural areas, enhanced safety for vehicles, and enriched entertainment experiences for mobile users. Featuring state-of-the-art research in the IoT field, this book can help answer the question of how to connect billions of diverse devices and enable seamless data collection and processing in future IoT. The content also provides insights regarding the significance of customizing use case-specific solutions as well as approaches of using various AI methods to empower IoT. This book targets researchers and graduate students working in the areas of electrical engineering, computing engineering, and computer science as a secondary textbook or reference. Professionals in industry who work in the field of IoT will also find this book useful.

Deep Learning for Internet of Things Infrastructure

Author : Uttam Ghosh
Publisher : CRC Press
ISBN 13 : 1000431959
Total Pages : 240 pages
Book Rating : 4.0/5 (4 download)

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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.

AI Models for Blockchain-Based Intelligent Networks in IoT Systems

Author : Bharat Bhushan
Publisher : Springer Nature
ISBN 13 : 3031319524
Total Pages : 396 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis AI Models for Blockchain-Based Intelligent Networks in IoT Systems by : Bharat Bhushan

Download or read book AI Models for Blockchain-Based Intelligent Networks in IoT Systems written by Bharat Bhushan and published by Springer Nature. This book was released on 2023-06-08 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this book is to explore various security paradigms such as Machine Learning, Big data, Cyber Physical Systems, and Blockchain to address both intelligence and reconfigurability in various IoT devices. The book further aims to address and analyze the state of the art of blockchain-based intelligent networks in IoT systems and related technologies including healthcare sector. AI can ease, optimize, and automate the blockchain-based decision-making process for better governance and higher performance in IoT systems. Considering the incredible progress made by AI models, a blockchain system powered by intelligent AI algorithms can detect the existence of any kind of attack and automatically invoke the required defense mechanisms. In case of unavoidable damage, AI models can help to isolate the compromised component from the blockchain platform and safeguard the overall system from crashing. Furthermore, AI models can also contribute toward the robustness and scalability of blockchain-based intelligent IoT networks. The book is designed to be the first-choice reference at university libraries, academic institutions, research and development centers, information technology centers, and any institutions interested in integration of AI and IoT. The intended audience of this book include UG/PG students, Ph.D. scholars of this fields, industry technologists, young entrepreneurs, professionals, network designers, data scientists, technology specialists, practitioners, and people who are interested in exploring the role of AI and blockchain technology in IoT systems.

Machine Learning and IoT for Intelligent Systems and Smart Applications

Author : Madhumathy P
Publisher : CRC Press
ISBN 13 : 1000484963
Total Pages : 243 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning and IoT for Intelligent Systems and Smart Applications by : Madhumathy P

Download or read book Machine Learning and IoT for Intelligent Systems and Smart Applications written by Madhumathy P and published by CRC Press. This book was released on 2021-11-17 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.