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Author: Sen Lin
Publisher: Springer Nature
ISBN: 3031023803
Category : Computers
Languages : en
Pages : 17
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Book Description
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.
Author: Sen Lin
Publisher: Springer Nature
ISBN: 3031023803
Category : Computers
Languages : en
Pages : 17
Get Book Here
Book Description
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.
Author: Sen Lin
Publisher:
ISBN: 9781681739922
Category :
Languages : en
Pages : 234
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Book Description
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.
Author: Nagarajan, G.
Publisher: IGI Global
ISBN: 1522585575
Category : Computers
Languages : en
Pages : 347
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Book Description
Edge computing is focused on devices and technologies that are attached to the internet of things (IoT). Identifying IoT use across a range of industries and measuring strategic values helps identify what technologies to pursue and can avoid wasted resources on deployments with limited values. Edge Computing and Computational Intelligence Paradigms for the IoT is a critical research book that provides a complete insight on the recent advancements and integration of intelligence in IoT. This book highlights various topics such as disaster prediction, governance, and healthcare. It is an excellent resource for researchers, working professionals, academicians, policymakers, and defense companies.
Author: Souvik Pal
Publisher: Springer Nature
ISBN: 3031583884
Category :
Languages : en
Pages : 392
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Book Description
Author: Pradip Debnath
Publisher: CRC Press
ISBN: 1000409813
Category : Computers
Languages : en
Pages : 232
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Book Description
Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.
Author: Pethuru Raj
Publisher: CRC Press
ISBN: 1000552691
Category : Computers
Languages : en
Pages : 329
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Book Description
The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI, edge computing, and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication
Author: Michael V. Hayden
Publisher: Penguin
ISBN: 0143109987
Category : Biography & Autobiography
Languages : en
Pages : 466
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Book Description
From the bestselling author of The Assault on Intelligence, an unprecedented high-level master narrative of America's intelligence wars, demonstrating in a time of new threats that espionage and the search for facts are essential to our democracy For General Michael Hayden, playing to the edge means playing so close to the line that you get chalk dust on your cleats. Otherwise, by playing back, you may protect yourself, but you will be less successful in protecting America. "Play to the edge" was Hayden's guiding principle when he ran the National Security Agency, and it remained so when he ran CIA. In his view, many shortsighted and uninformed people are quick to criticize, and this book will give them much to chew on but little easy comfort; it is an unapologetic insider's look told from the perspective of the people who faced awesome responsibilities head on, in the moment. How did American intelligence respond to terrorism, a major war and the most sweeping technological revolution in the last 500 years? What was NSA before 9/11 and how did it change in its aftermath? Why did NSA begin the controversial terrorist surveillance program that included the acquisition of domestic phone records? What else was set in motion during this period that formed the backdrop for the infamous Snowden revelations in 2013? As Director of CIA in the last three years of the Bush administration, Hayden had to deal with the rendition, detention and interrogation program as bequeathed to him by his predecessors. He also had to ramp up the agency to support its role in the targeted killing program that began to dramatically increase in July 2008. This was a time of great crisis at CIA, and some agency veterans have credited Hayden with actually saving the agency. He himself won't go that far, but he freely acknowledges that CIA helped turn the American security establishment into the most effective killing machine in the history of armed conflict. For 10 years, then, General Michael Hayden was a participant in some of the most telling events in the annals of American national security. General Hayden's goals are in writing this book are simple and unwavering: No apologies. No excuses. Just what happened. And why. As he writes, "There is a story here that deserves to be told, without varnish and without spin. My view is my view, and others will certainly have different perspectives, but this view deserves to be told to create as complete a history as possible of these turbulent times. I bear no grudges, or at least not many, but I do want this to be a straightforward and readable history for that slice of the American population who depend on and appreciate intelligence, but who do not have the time to master its many obscure characteristics."
Author: Xiaofei Wang
Publisher: Springer Nature
ISBN: 3031101863
Category : Technology & Engineering
Languages : en
Pages : 118
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Book Description
This book examines whether the integration of edge intelligence (EI) and blockchain (BC) can open up new horizons for providing ubiquitous intelligent services. Accordingly, the authors conduct a summarization of the recent research efforts on the existing works for EI and BC, further painting a comprehensive picture of the limitation of EI and why BC could benefit EI. To examine how to integrate EI and BC, the authors discuss the BC-driven EI and tailoring BC to EI, including an overview, motivations, and integrated frameworks. Finally, some challenges and future directions are explored. The book explores the technologies associated with the integrated system between EI and BC, and further bridges the gap between immature BC and EI-amicable BC. Explores the integration of edge intelligence (EI) and blockchain (BC), including their integrated motivations, frameworks and challenges; Presents how BC-driven EI can realize computing-power management, data administration, and model optimization; Describes how to tailor BC to better support EI, including flexible consensus protocol, effective incentive mechanism, intellectuality smart contract, and scalable BC system tailoring; Presents some key research challenges and future directions for the integrated system.
Author: Javid Taheri
Publisher: Springer Nature
ISBN: 3031221559
Category : Computers
Languages : en
Pages : 254
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Book Description
This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.
Author: Bharat S Chaudhari
Publisher: Elsevier
ISBN: 0443222037
Category : Computers
Languages : en
Pages : 520
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Book Description
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.
