Embedded Artificial Intelligence
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Embedded Artificial Intelligence
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Author : Ovidiu Vermesan
language : en
Publisher:
Release Date : 2022
Embedded Artificial Intelligence written by Ovidiu Vermesan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Artificial intelligence categories.
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 or spiking neural network (SNN) 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 book0́9s 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 Artificial Intelligence
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Author : Arpita Nath Boruah
language : en
Publisher: CRC Press
Release Date : 2025-03-28
Embedded Artificial Intelligence written by Arpita Nath Boruah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.
This book explores the role of embedded AI in revolutionizing industries such as healthcare, transportation, manufacturing, and retail. It begins by introducing the fundamentals of AI and embedded systems and specific challenges and opportunities. A key focus of this book is developing efficient and effective algorithms and models for embedded AI systems, as embedded systems have limited processing power, memory, and storage. It discusses a variety of techniques for optimizing algorithms and models for embedded systems, including hardware acceleration, model compression, and quantization. Key features: • Explores security experiments in emerging post‐CMOS technologies using AI, including side channel attack‐resistant embedded systems. • Discusses different hardware and software platforms available for developing embedded AI applications, as well as the various techniques used to design and implement these systems. • Considers ethical and societal implications of embedded AI vis‐a‐vis the need for responsible development and deployment of embedded AI systems. • Focuses on application‐based research and case studies to develop embedded AI systems for real‐life applications. • Examines high‐end parallel systems to run complex AI algorithms and comprehensive functionality while maintaining portability and power efficiency. This reference book is for students, researchers, and professionals interested in embedded AI and relevant branches of computer science, electrical engineering, or artificial intelligence.
Embedded Artificial Intelligence
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Author : Arpita Nath Boruah
language : en
Publisher:
Release Date : 2025
Embedded Artificial Intelligence written by Arpita Nath Boruah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Artificial intelligence categories.
"This book explores the role of Embedded AI in revolutionising industries such as healthcare, transportation, manufacturing, retail. It begins by introducing the fundamentals of AI and embedded systems and specific challenges and opportunities. A key focus of the book is developing efficient and effective algorithms and models for embedded AI systems, as embedded systems have limited processing power, memory, and storage. It discusses a variety of techniques for optimising algorithms and models for embedded systems, including hardware acceleration, model compression, and quantisation. Explores security experiments in emerging post-CMOS technologies using AI, including side-channel attack-resistant embedded systems Discusses different hardware and software platforms available for developing embedded AI applications, as well as the various techniques used to design and implement these systems Considers ethical and societal implications of embedded AI vis-a-vis the need for responsible development and deployment of embedded AI systems Focuses on application-based research and case studies to develop embedded AI systems for real-life applications Examines high-end parallel systems to run complex AI algorithms and comprehensive functionality while maintaining portability and power-efficiency This reference book is for students, researchers and professionals interested in Embedded AI, and relevant branches of computer science, electrical engineering, or artificial intelligence"--
Embedded Artificial Intelligence Bridging The Gap Between Hardware And Deep Learning
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Author : François Rivet
language : en
Publisher: CRC Press
Release Date : 2026-01-26
Embedded Artificial Intelligence Bridging The Gap Between Hardware And Deep Learning written by François Rivet and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-26 with Computers categories.
The IEEE CAS Seasonal School on Technologies for Artificial Intelligence tackles the critical skill gap between embedded technology and deep learning. Supported by European projects FVLLMONTI, HERMES, and RadioSpin, this event fosters a transdisciplinary community focused on embedded artificial intelligence. Modern AI and deep learning often require extensive computing resources, impacting security and privacy. Embedded AI offers a solution by running machine learning models on edge devices, necessitating optimized software–hardware integration and energy-efficient neural network hardware. This school equips participants with the skills to innovate in circuit design and execute data-intensive applications on limited-resource devices. The curriculum covers neural network basics, hardware enhancement, electrical characterization, and neuromorphic device design. Key topics include 6G transceiver optimization, transformer architectures for machine translation, and intelligent sensors for practical applications like RF fingerprint recognition and breast cancer detection.
Embedded Artificial Intelligence
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Author : Bin Li
language : en
Publisher: Springer Nature
Release Date : 2024-09-06
Embedded Artificial Intelligence written by Bin Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-06 with Computers categories.
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.
Ai At The Edge
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Author : Daniel Situnayake
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-01-10
Ai At The Edge written by Daniel Situnayake and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-10 with Computers categories.
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
Tinyml Cookbook
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Author : Gian Marco Iodice
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-01
Tinyml Cookbook written by Gian Marco Iodice and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-01 with Computers categories.
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 Systems And Artificial Intelligence
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Author : Vikrant Bhateja
language : en
Publisher: Springer Nature
Release Date : 2020-04-07
Embedded Systems And Artificial Intelligence written by Vikrant Bhateja and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-07 with Technology & Engineering categories.
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.
Learning In Embedded Systems
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Author : Leslie Pack Kaelbling
language : en
Publisher: MIT Press
Release Date : 1993
Learning In Embedded Systems written by Leslie Pack Kaelbling and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.
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.
Embedded Devices And Internet Of Things
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Author : Adesh Kumar
language : en
Publisher: CRC Press
Release Date : 2024-09-11
Embedded Devices And Internet Of Things written by Adesh Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Technology & Engineering categories.
The text comprehensively discusses machine-to-machine communication in real-time, low-power system design and estimation using field programmable gate arrays, PID, hardware, accelerators, and software integration for service applications. It further covers the recent advances in embedded computing and IoT for healthcare systems. The text explains the use of low-power devices such as microcontrollers in executing deep neural networks, and other machine learning techniques. This book: Discusses the embedded system software and hardware methodologies for system-on-chip and FPGA Illustrates low-power embedded applications, AI-based system design, PID control design, and CNN hardware design Highlights the integration of advanced 5G communication technologies with embedded systems Explains weather prediction modeling, embedded machine learning, and RTOS Highlights the significance of machine-learning techniques on the Internet of Things (IoT), real-time embedded system design, communication, and healthcare applications, and provides insights on IoT applications in education, fault attacks, security concerns, AI integration, banking, blockchain, intelligent tutoring systems, and smart technologies It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, and computer engineering.