Building Scalable Edge Ai Solutions For The Internet Of Things
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Building Scalable Edge AI Solutions for the Internet of Things
Building Scalable Edge AI Solutions for the Internet of Things" explores the convergence of IoT, edge computing, and AI, providing a practical guide to developing and deploying intelligent edge solutions. The book begins by establishing foundational concepts, explaining the limitations of cloud-centric IoT architectures and introducing the benefits of edge computing and Edge AI, such as reduced latency, bandwidth efficiency, and enhanced privacy. It then delves into the building blocks of Edge AI solutions, covering data acquisition and preprocessing techniques optimized for resource-constrained devices, model selection and compression strategies, and an overview of relevant frameworks and hardware platforms like MCUs, MPUs, GPUs, and FPGAs. The book further provides a practical development approach, detailing the steps from problem definition and data preparation to model training, evaluation, and deployment on edge devices. It emphasizes the importance of robust deployment strategies, including OTA updates, device management tools, and crucial security considerations. Finally, the book examines advanced topics like real-time Edge AI applications in industrial automation, robotics, and autonomous systems, along with scalability and orchestration strategies for large deployments. It concludes by exploring future trends, including emerging hardware and software, the role of 5G, and the ethical implications of Edge AI, advocating for responsible AI development.
IoT and Edge Computing for Architects
Create scalable IoT and edge computing solutions with practical architectural strategies, robust communication protocols, and integrated analytics support for informed decision-making Key Features Build robust IoT and edge computing systems using real-world architectural strategies Explore a comprehensive range of technologies—from sensors and RF to cloud infrastructure and analytics Gain the insights needed to make informed technical decisions across communication protocols, security, and system design Book DescriptionIndustries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices. IoT and Edge Computing for Architects, 2E encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. The book wraps up the analytics portion with the application of statistical analysis, complex event processing, and deep learning models. The book then concludes by providing a holistic view of IoT security, cryptography, and shell security in addition to software-defined perimeters and blockchains.What you will learn Understand the role and scope of architecting a successful IoT deployment Scan the landscape of IoT technologies, from sensors to the cloud and more See the trade-offs in choices of protocols and communications in IoT deployments Become familiar with the terminology needed to work in the IoT space Broaden your skills in the multiple engineering domains necessary for the IoT architect Implement best practices to ensure reliability, scalability, and security in your IoT infrastructure Who this book is for This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, technologies, and trade-offs, and develop a 50,000-foot view of IoT architecture. An understanding of the architectural side of IoT is necessary.
Artificial Intelligence for IoT Cookbook
Author: Michael Roshak
language: en
Publisher: Packt Publishing Ltd
Release Date: 2021-03-05
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.