Embedded Artificial Intelligence

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Embedded Artificial Intelligence

Ovidiu Vermesan,Mario Diaz Nava,Björn Debaillie
Embedded Artificial Intelligence Book PDF

Author : Ovidiu Vermesan,Mario Diaz Nava,Björn Debaillie
Publisher : CRC Press
Page : 143 pages
File Size : 40,8 Mb
Release : 2023-05-05
Category : Computers
ISBN : 9781000881912

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Embedded Artificial Intelligence by Ovidiu Vermesan,Mario Diaz Nava,Björn Debaillie Pdf

Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.

Embedded Systems and Artificial Intelligence

Vikrant Bhateja,Suresh Chandra Satapathy,Hassan Satori
Embedded Systems and Artificial Intelligence Book PDF

Author : Vikrant Bhateja,Suresh Chandra Satapathy,Hassan Satori
Publisher : Springer Nature
Page : 880 pages
File Size : 55,8 Mb
Release : 2020-04-07
Category : Technology & Engineering
ISBN : 9789811509476

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Embedded Systems and Artificial Intelligence by Vikrant Bhateja,Suresh Chandra Satapathy,Hassan Satori Pdf

This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2–3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.

Embedded Artificial Intelligence

Bin Li
Embedded Artificial Intelligence Book PDF

Author : Bin Li
Publisher : Springer
Page : 0 pages
File Size : 46,7 Mb
Release : 2024-09-18
Category : Computers
ISBN : 9819750377

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Embedded Artificial Intelligence by Bin Li Pdf

This book focuses on the emerging topic of embedded artificial intelligence and provides a systematic summary of its principles, platforms, and practices. In the section on principles, it analyzes three main approaches for implementing embedded artificial intelligence: cloud computing mode, local mode, and local-cloud collaborative mode. The book identifies five essential components for implementing embedded artificial intelligence: embedded AI accelerator chips, lightweight neural network algorithms, model compression techniques, compiler optimization techniques, and multi-level cascaded application frameworks. The platform section introduces mainstream embedded AI accelerator chips and software frameworks currently used in the industry. The practical part outlines the development process of embedded artificial intelligence and showcases real-world application examples with accompanying code. As a comprehensive guide to the emerging field of embedded artificial intelligence, the book offers rich and in-depth content, a clear and logical structure, and a balanced approach to both theoretical analysis and practical applications. It provides significant reference value and can serve as an introductory and reference guide for researchers, scholars, students, engineers, and professionals interested in studying and implementing embedded artificial intelligence.

TinyML

Pete Warden,Daniel Situnayake
TinyML Book PDF

Author : Pete Warden,Daniel Situnayake
Publisher : O'Reilly Media
Page : 504 pages
File Size : 40,9 Mb
Release : 2019-12-16
Category : Computers
ISBN : 9781492052012

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TinyML by Pete Warden,Daniel Situnayake Pdf

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

Deep Learning on Microcontrollers

Atul Krishna Gupta,Dr. Siva Prasad Nandyala
Deep Learning on Microcontrollers Book PDF

Author : Atul Krishna Gupta,Dr. Siva Prasad Nandyala
Publisher : BPB Publications
Page : 346 pages
File Size : 48,8 Mb
Release : 2023-04-15
Category : Computers
ISBN : 9789355518057

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Deep Learning on Microcontrollers by Atul Krishna Gupta,Dr. Siva Prasad Nandyala Pdf

A step-by-step guide that will teach you how to deploy TinyML on microcontrollers KEY FEATURES ● Deploy machine learning models on edge devices with ease. ● Leverage pre-built AI models and deploy them without writing any code. ● Create smart and efficient IoT solutions with TinyML. DESCRIPTION TinyML, or Tiny Machine Learning, is used to enable machine learning on resource-constrained devices, such as microcontrollers and embedded systems. If you want to leverage these low-cost, low-power but strangely powerful devices, then this book is for you. This book aims to increase accessibility to TinyML applications, particularly for professionals who lack the resources or expertise to develop and deploy them on microcontroller-based boards. The book starts by giving a brief introduction to Artificial Intelligence, including classical methods for solving complex problems. It also familiarizes you with the different ML model development and deployment tools, libraries, and frameworks suitable for embedded devices and microcontrollers. The book will then help you build an Air gesture digit recognition system using the Arduino Nano RP2040 board and an AI project for recognizing keywords using the Syntiant TinyML board. Lastly, the book summarizes the concepts covered and provides a brief introduction to topics such as zero-shot learning, one-shot learning, federated learning, and MLOps. By the end of the book, you will be able to develop and deploy end-to-end Tiny ML solutions with ease. WHAT YOU WILL LEARN ● Learn how to build a Keyword recognition system using the Syntiant TinyML board. ● Learn how to build an air gesture digit recognition system using the Arduino Nano RP2040. ● Learn how to test and deploy models on Edge Impulse and Arduino IDE. ● Get tips to enhance system-level performance. ● Explore different real-world use cases of TinyML across various industries. WHO THIS BOOK IS FOR The book is for IoT developers, System engineers, Software engineers, Hardware engineers, and professionals who are interested in integrating AI into their work. This book is a valuable resource for Engineering undergraduates who are interested in learning about microcontrollers and IoT devices but may not know where to begin. TABLE OF CONTENTS 1. Introduction to AI 2. Traditional ML Lifecycle 3. TinyML Hardware and Software Platforms 4. End-to-End TinyML Deployment Phases 5. Real World Use Cases 6. Practical Experiments with TinyML 7. Advance Implementation with TinyML Board 8. Continuous Improvement 9. Conclusion

Learning in Embedded Systems

Leslie Pack Kaelbling
Learning in Embedded Systems Book PDF

Author : Leslie Pack Kaelbling
Publisher : MIT Press
Page : 206 pages
File Size : 54,8 Mb
Release : 1993
Category : Computers
ISBN : 0262111748

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Learning in Embedded Systems by Leslie Pack Kaelbling Pdf

Learning to perform complex action strategies is an important problem in the fields of artificial intelligence, robotics and machine learning. Presenting interesting, new experimental results, Learning in Embedded Systems explores algorithms that learn efficiently from trial and error experience with an external world. The text is a detailed exploration of the problem of learning action strategies in the context of designing embedded systems that adapt their behaviour to a complex, changing environment. Such systems include mobile robots, factory process controllers and long-term software databases.

Beginning Artificial Intelligence with the Raspberry Pi

Donald J. Norris
Beginning Artificial Intelligence with the Raspberry Pi Book PDF

Author : Donald J. Norris
Publisher : Apress
Page : 379 pages
File Size : 47,6 Mb
Release : 2017-06-05
Category : Computers
ISBN : 9781484227435

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Beginning Artificial Intelligence with the Raspberry Pi by Donald J. Norris Pdf

Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.

Embedded Deep Learning

Bert Moons,Daniel Bankman,Marian Verhelst
Embedded Deep Learning Book PDF

Author : Bert Moons,Daniel Bankman,Marian Verhelst
Publisher : Springer
Page : 206 pages
File Size : 48,5 Mb
Release : 2018-10-23
Category : Technology & Engineering
ISBN : 9783319992235

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Embedded Deep Learning by Bert Moons,Daniel Bankman,Marian Verhelst Pdf

This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning. Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devices; Discusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy – applications, algorithms, hardware architectures, and circuits – supported by real silicon prototypes; Elaborates on how to design efficient Convolutional Neural Network processors, exploiting parallelism and data-reuse, sparse operations, and low-precision computations; Supports the introduced theory and design concepts by four real silicon prototypes. The physical realization’s implementation and achieved performances are discussed elaborately to illustrated and highlight the introduced cross-layer design concepts.

The AI Book

Ivana Bartoletti,Anne Leslie,Shân M. Millie
The AI Book Book PDF

Author : Ivana Bartoletti,Anne Leslie,Shân M. Millie
Publisher : John Wiley & Sons
Page : 782 pages
File Size : 53,6 Mb
Release : 2020-04-09
Category : Business & Economics
ISBN : 9781119551928

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The AI Book by Ivana Bartoletti,Anne Leslie,Shân M. Millie Pdf

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

AI at the Edge

Daniel Situnayake,Jenny Plunkett
AI at the Edge Book PDF

Author : Daniel Situnayake,Jenny Plunkett
Publisher : "O'Reilly Media, Inc."
Page : 540 pages
File Size : 46,9 Mb
Release : 2023-01-10
Category : Computers
ISBN : 9781098120160

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AI at the Edge by Daniel Situnayake,Jenny Plunkett Pdf

Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target--from ultra-low power microcontrollers to embedded Linux devices. This practical guide gives engineering professionals, including product managers and technology leaders, an end-to-end framework for solving real-world industrial, commercial, and scientific problems with edge AI. You'll explore every stage of the process, from data collection to model optimization to tuning and testing, as you learn how to design and support edge AI and embedded ML products. Edge AI is destined to become a standard tool for systems engineers. This high-level road map helps you get started. Develop your expertise in AI and ML for edge devices Understand which projects are best solved with edge AI Explore key design patterns for edge AI apps Learn an iterative workflow for developing AI systems Build a team with the skills to solve real-world problems Follow a responsible AI process to create effective products

Artificial Intelligence and Hardware Accelerators

Ashutosh Mishra,Jaekwang Cha,Hyunbin Park,Shiho Kim
Artificial Intelligence and Hardware Accelerators Book PDF

Author : Ashutosh Mishra,Jaekwang Cha,Hyunbin Park,Shiho Kim
Publisher : Springer Nature
Page : 358 pages
File Size : 50,9 Mb
Release : 2023-03-15
Category : Technology & Engineering
ISBN : 9783031221705

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Artificial Intelligence and Hardware Accelerators by Ashutosh Mishra,Jaekwang Cha,Hyunbin Park,Shiho Kim Pdf

This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Sudeep Pasricha,Muhammad Shafique
Embedded Machine Learning for Cyber Physical IoT and Edge Computing Book PDF

Author : Sudeep Pasricha,Muhammad Shafique
Publisher : Springer Nature
Page : 481 pages
File Size : 42,9 Mb
Release : 2023-10-09
Category : Technology & Engineering
ISBN : 9783031399329

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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing by Sudeep Pasricha,Muhammad Shafique Pdf

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

Systems Engineering and Artificial Intelligence

William F. Lawless,Ranjeev Mittu,Donald A. Sofge,Thomas Shortell,Thomas A. McDermott
Systems Engineering and Artificial Intelligence Book PDF

Author : William F. Lawless,Ranjeev Mittu,Donald A. Sofge,Thomas Shortell,Thomas A. McDermott
Publisher : Springer Nature
Page : 566 pages
File Size : 46,5 Mb
Release : 2021-11-02
Category : Computers
ISBN : 9783030772833

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Systems Engineering and Artificial Intelligence by William F. Lawless,Ranjeev Mittu,Donald A. Sofge,Thomas Shortell,Thomas A. McDermott Pdf

This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.

TinyML Cookbook

Gian Marco Iodice
TinyML Cookbook Book PDF

Author : Gian Marco Iodice
Publisher : Packt Publishing Ltd
Page : 344 pages
File Size : 47,8 Mb
Release : 2022-04-01
Category : Computers
ISBN : 9781801812634

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TinyML Cookbook by Gian Marco Iodice Pdf

Work through over 50 recipes to develop smart applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico using the power of machine learning Key Features Train and deploy ML models on Arduino Nano 33 BLE Sense and Raspberry Pi Pico Work with different ML frameworks such as TensorFlow Lite for Microcontrollers and Edge Impulse Explore cutting-edge technologies such as microTVM and Arm Ethos-U55 microNPU Book DescriptionThis book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you’ll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game. By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.What you will learn Understand the relevant microcontroller programming fundamentals Work with real-world sensors such as the microphone, camera, and accelerometer Run on-device machine learning with TensorFlow Lite for Microcontrollers Implement an app that responds to human voice with Edge Impulse Leverage transfer learning to classify indoor rooms with Arduino Nano 33 BLE Sense Create a gesture-recognition app with Raspberry Pi Pico Design a CIFAR-10 model for memory-constrained microcontrollers Run an image classifier on a virtual Arm Ethos-U55 microNPU with microTVM Who this book is for This book is for machine learning developers/engineers interested in developing machine learning applications on microcontrollers through practical examples quickly. Basic familiarity with C/C++, the Python programming language, and the command-line interface (CLI) is required. However, no prior knowledge of microcontrollers is necessary.

Embedded Automation in Human-Agent Environment

Jeff Tweedale,Lakhmi C. Jain
Embedded Automation in Human Agent Environment Book PDF

Author : Jeff Tweedale,Lakhmi C. Jain
Publisher : Springer Science & Business Media
Page : 223 pages
File Size : 55,7 Mb
Release : 2011-09-25
Category : Technology & Engineering
ISBN : 9783642226762

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Embedded Automation in Human-Agent Environment by Jeff Tweedale,Lakhmi C. Jain Pdf

This research book proposes a general conceptual framework for the development of automation in human-agents environments that will allow human- agent teams to work effectively and efficiently. We examine various schemes to implement artificial intelligence techniques in agents. The text is directed to the scientists, application engineers, professors and students of all disciplines, interested in the agency methodology and applications.