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Author: Agus Kurniawan
Publisher:
ISBN: 9781484264539
Category : Artificial intelligence
Languages : en
Pages :
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Book Description
Explore the capabilities of the NVIDIA Jetson Nano, an IoT device designed to perform computations like a computer desktop. This book will show you how to build your first project and optimize your devices, programs, and daily activities with the AI computation abilities of the Jetson Nano. This board consists of CPU Quad-core ARM A57 @ 1.43 GHz and GPU 128-core Maxwell. With this hardware specification, the board can run multiple neural networks in parallel for complex AI applications. With the integrated sensor and actuators, this board enables stronger IoT solutions and provides more advanced capabilities. Discover how develop complex IoT projects with the Jetson Nano today. You will: Set up NVIDIA Jetson Nano device Build applications like image classification, object detection, segmentation, and speech processing Use the Jetson Nano to process daily computer activities such as browsing the internet, checking emails, or playing music and videos Implement machine learning computations into your projects.
Author: Agus Kurniawan
Publisher:
ISBN: 9781484264539
Category : Artificial intelligence
Languages : en
Pages :
Get Book Here
Book Description
Explore the capabilities of the NVIDIA Jetson Nano, an IoT device designed to perform computations like a computer desktop. This book will show you how to build your first project and optimize your devices, programs, and daily activities with the AI computation abilities of the Jetson Nano. This board consists of CPU Quad-core ARM A57 @ 1.43 GHz and GPU 128-core Maxwell. With this hardware specification, the board can run multiple neural networks in parallel for complex AI applications. With the integrated sensor and actuators, this board enables stronger IoT solutions and provides more advanced capabilities. Discover how develop complex IoT projects with the Jetson Nano today. You will: Set up NVIDIA Jetson Nano device Build applications like image classification, object detection, segmentation, and speech processing Use the Jetson Nano to process daily computer activities such as browsing the internet, checking emails, or playing music and videos Implement machine learning computations into your projects.
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: Ms. DEBOSREE GHOSH
Publisher: kitab writing publication
ISBN: 9358682167
Category : Antiques & Collectibles
Languages : en
Pages : 299
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Book Description
This comprehensive guide dig into the fundamentals of IoT technology, providing students with a thorough understanding of its concepts, applications, and business implications. It equips them with the knowledge and skills necessary to navigate the rapidly evolving IoT landscape. Through engaging learning experiences, students gain knowledge about the strategic implementation and management of IoT solutions, preparing them for success in today's technology-driven world.
Author: Jivan S. Parab
Publisher: Springer Nature
ISBN: 9811994668
Category : Technology & Engineering
Languages : en
Pages : 206
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Book Description
The book comprehensively covers the most important applications of the internet of things (IoT) using Python programming on Raspberry pi, Micropython Py Board, and NVIDIA Jetson Board. The authors have used an immersive ‘hands-on’ approach to help readers gain expertise in developing working code for real-world IoT applications. The book focuses on industry-standard embedded platforms for IoT applications. It also gives a glimpse of python programming and setup configuration of these embedded platforms. The later chapter highlights basic interface applications with Raspberry Pi. Exclusive advanced IoT applications on the Micropython Pyboard are also covered. The last two chapters deal with the NVIDIA Jetson Nano board programming for machine learning applications with FoG/cloud computing. The various IoT applications with different embedded platforms in this volume are best-suited for undergraduate/postgraduate students and researchers who want to get exposed to python programming for IoT applications. This book will enable readers to design their own embedded IoT products.
Author: Tran Khanh Dang
Publisher: Springer Nature
ISBN: 9811980691
Category : Computers
Languages : en
Pages : 773
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Book Description
This book constitutes the refereed proceedings of the 9th International Conference on Future Data and Security Engineering, FDSE 2022, held in Ho Chi Minh City, Vietnam, during November 23–25, 2022. The 41 full papers(including 4 invited keynotes) and 12 short papers included in this book were carefully reviewed and selected from 170 submissions. They were organized in topical sections as follows: invited keynotes; big data analytics and distributed systems; security and privacy engineering; machine learning and artificial intelligence for security and privacy; smart city and industry 4.0 applications; data analytics and healthcare systems; and security and data engineering.
Author: Jose Martinez-Carranza
Publisher: CRC Press
ISBN: 1003827438
Category : Computers
Languages : en
Pages : 386
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Book Description
This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of artificial intelligence, cryptography, embedded hardware, electronics, the Internet of Things, and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research. Features Provides details of applications using machine learning methods to solve real problems in engineering Discusses new developments in the areas of complex and unmanned systems Includes details of hardware/software implementation of machine learning methods Includes examples of applications of different machine learning methods for future lines for research in the hot topic areas of submarines, drones, robots, cryptography, electronics, healthcare, and the Internet of Things This book can be used by graduate students, industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling, simulation, and optimization of complex systems, cryptography, electronics, healthcare, control systems, Internet of Things, security, and unmanned systems such as submarines, drones, and robots.
Author: Atul Krishna Gupta
Publisher: BPB Publications
ISBN: 9355518056
Category : Computers
Languages : en
Pages : 346
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Book Description
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
Author: Shunli Zhang
Publisher: Springer Nature
ISBN: 303177003X
Category :
Languages : en
Pages : 145
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Book Description
Author: Michael Roshak
Publisher: Packt Publishing Ltd
ISBN: 1838986499
Category : Computers
Languages : en
Pages : 252
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Book Description
Implement machine learning and deep learning techniques to perform predictive analytics on real-time IoT data Key FeaturesDiscover quick solutions to common problems that you'll face while building smart IoT applicationsImplement advanced techniques such as computer vision, NLP, and embedded machine learningBuild, maintain, and deploy machine learning systems to extract key insights from IoT dataBook Description Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications. Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You'll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you'll learn how to deploy models and improve their performance with ease. By the end of this book, you'll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems. What you will learnExplore various AI techniques to build smart IoT solutions from scratchUse machine learning and deep learning techniques to build smart voice recognition and facial detection systemsGain insights into IoT data using algorithms and implement them in projectsPerform anomaly detection for time series data and other types of IoT dataImplement embedded systems learning techniques for machine learning on small devicesApply pre-trained machine learning models to an edge deviceDeploy machine learning models to web apps and mobile using TensorFlow.js and JavaWho this book is for If you're an IoT practitioner looking to incorporate AI techniques to build smart IoT solutions without having to trawl through a lot of AI theory, this AI IoT book is for you. Data scientists and AI developers who want to build IoT-focused AI solutions will also find this book useful. Knowledge of the Python programming language and basic IoT concepts is required to grasp the concepts covered in this artificial intelligence book more effectively.
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.
