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Author: Xiaofei Wang
Publisher: Springer Nature
ISBN: 9811561869
Category : Computers
Languages : en
Pages : 156
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Book Description
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.
Author: Xiaofei Wang
Publisher: Springer Nature
ISBN: 9811561869
Category : Computers
Languages : en
Pages : 156
Get Book Here
Book Description
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.
Author: Pete Warden
Publisher: O'Reilly Media
ISBN: 1492052019
Category : Computers
Languages : en
Pages : 504
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Book Description
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size
Author: Yuanming Shi
Publisher: Elsevier
ISBN: 0128238178
Category : Computers
Languages : en
Pages : 206
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Book Description
Front Cover -- Mobile Edge Artificial Intelligence -- Copyright -- Contents -- List of figures -- Biography -- Yuanming Shi -- Kai Yang -- Zhanpeng Yang -- Yong Zhou -- Preface -- Acknowledgments -- Part 1 Introduction and overview -- 1 Motivations and organization -- 1.1 Motivations -- 1.2 Organization -- References -- 2 Primer on artificial intelligence -- 2.1 Basics of machine learning -- 2.1.1 Supervised learning -- 2.1.1.1 Logistic regression -- 2.1.1.2 Support vector machine -- 2.1.1.3 Decision tree -- 2.1.1.4 k-Nearest neighbors method -- 2.1.1.5 Neural network -- 2.1.2 Unsupervised learning -- 2.1.2.1 k-Means algorithm -- 2.1.2.2 Principal component analysis -- 2.1.2.3 Autoencoder -- 2.1.3 Reinforcement learning -- 2.1.3.1 Q-learning -- 2.1.3.2 Policy gradient -- 2.2 Models of deep learning -- 2.2.1 Convolutional neural network -- 2.2.2 Recurrent neural network -- 2.2.3 Graph neural network -- 2.2.4 Generative adversarial network -- 2.3 Summary -- References -- 3 Convex optimization -- 3.1 First-order methods -- 3.1.1 Gradient method for unconstrained problems -- 3.1.2 Gradient method for constrained problems -- 3.1.3 Subgradient descent method -- 3.1.4 Mirror descent method -- 3.1.5 Proximal gradient method -- 3.1.6 Accelerated gradient method -- 3.1.7 Smoothing for nonsmooth optimization -- 3.1.8 Dual and primal-dual methods -- 3.1.9 Alternating direction method of multipliers -- 3.1.10 Stochastic gradient method -- 3.2 Second-order methods -- 3.2.1 Newton's method -- 3.2.2 Quasi-Newton method -- 3.2.3 Gauss-Newton method -- 3.2.4 Natural gradient method -- 3.3 Summary -- References -- 4 Mobile edge AI -- 4.1 Overview -- 4.2 Edge inference -- 4.2.1 On-device inference -- 4.2.2 Edge inference via computation offloading -- 4.2.2.1 Server-based edge inference -- 4.2.2.2 Device-edge joint inference -- 4.3 Edge training.
Author: Pradip Debnath
Publisher: CRC Press
ISBN: 1000409813
Category : Computers
Languages : en
Pages : 233
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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: David B. Fogel
Publisher: Morgan Kaufmann
ISBN: 9781558607835
Category : Computers
Languages : en
Pages : 430
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Book Description
This book explains how a computer, by replicating the processes of Darwinian evolution, taught itself to play checkers far better than its creators could have programmed it to play. Fogel (editor, IEEE Transactions on Evolutionary Computation) considers the implications for evolutionary computations and artificial intelligence. Diagrams illustrate the evolutionary and computational processes at work, and the course of various games of checkers. Annotation copyrighted by Book News, Inc., Portland, OR.
Author: Katie King
Publisher: Kogan Page Publishers
ISBN: 0749483407
Category : Business & Economics
Languages : en
Pages : 225
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Book Description
Artificial intelligence (AI) is paving the way for the future of marketing and business transformation, yet many organizations struggle to know exactly how and where to integrate it. This book is the ultimate guide to embracing the opportunity that AI can bring for your marketing. With AI forecasted to boost global GDP by 14% by 2030, an efficient and sustainable AI marketing strategy is now essential to avoid losing the competitive edge. Using Artificial Intelligence in Marketing provides the definitive, practical framework needed for marketers to identify, apply and embrace the opportunity to maximize the results and business advancement that AI can bring. Streamlining efficiencies into every business practice, AI automates simpler, repetitive tasks with unrivalled accuracy, allowing sales and marketing teams to return their attention to where human interaction is most valuable: strategy, creativity and personal connection. Using Artificial Intelligence in Marketing outlines key marketing benefits such as accurate market research samples, immediate big data insights and brand-safe content creation, right through to the on-demand customer service that is now expected 24/7. It also explores the inevitable myths, concerns and ethical questions that can arise from the large-scale adoption of AI. This book is an essential read for every 21st century marketer.
Author: Rajiv Pandey
Publisher: Academic Press
ISBN: 0128240555
Category : Science
Languages : en
Pages : 516
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Book Description
Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. - Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing - Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers - Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
Author: Sanjay Misra
Publisher: Springer Nature
ISBN: 3030808211
Category : Computers
Languages : en
Pages : 358
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Book Description
This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.
Author: Ajith Abraham
Publisher: Academic Press
ISBN: 0128236957
Category : Technology & Engineering
Languages : en
Pages : 578
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Book Description
AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture. Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming. - Integrates sustainable agriculture, Greenhouse IOT, precision agriculture, crops monitoring, crops controlling to prediction, livestock monitoring, and farm management - Presents data mining techniques for precision agriculture, including weather prediction, plant disease prediction, and decision support for crop and soil selection - Promotes the importance and uses in managing the agro ecosystem for food security - Emphasizes low energy usage options for low cost and environmental sustainability
