Hands On Edge Analytics With Azure Iot
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Hands-On Edge Analytics with Azure IoT
Design, secure, and protect the privacy of edge analytics applications using platforms and tools such as Microsoft's Azure IoT Edge, MicroPython, and Open Source Computer Vision (OpenCV) Key FeaturesBecome well-versed with best practices for implementing automated analytical computationsDiscover real-world examples to extend cloud intelligenceDevelop your skills by understanding edge analytics and applying it to research activitiesBook Description Edge analytics has gained attention as the IoT model for connected devices rises in popularity. This guide will give you insights into edge analytics as a data analysis model, and help you understand why it’s gaining momentum. You'll begin with the key concepts and components used in an edge analytics app. Moving ahead, you'll delve into communication protocols to understand how sensors send their data to computers or microcontrollers. Next, the book will demonstrate how to design modern edge analytics apps that take advantage of the processing power of modern single-board computers and microcontrollers. Later, you'll explore Microsoft Azure IoT Edge, MicroPython, and the OpenCV visual recognition library. As you progress, you'll cover techniques for processing AI functionalities from the server side to the sensory side of IoT. You'll even get hands-on with designing a smart doorbell system using the technologies you’ve learned. To remove vulnerabilities in the overall edge analytics architecture, you'll discover ways to overcome security and privacy challenges. Finally, you'll use tools to audit and perform real-time monitoring of incoming data and generate alerts for the infrastructure. By the end of this book, you'll have learned how to use edge analytics programming techniques and be able to implement automated analytical computations. What you will learnDiscover the key concepts and architectures used with edge analyticsUnderstand how to use long-distance communication protocols for edge analyticsDeploy Microsoft Azure IoT Edge to a Raspberry PiCreate Node-RED dashboards with MQTT and Text to Speech (TTS)Use MicroPython for developing edge analytics appsExplore various machine learning techniques and discover how machine learning is related to edge analyticsUse camera and vision recognition algorithms on the sensory side to design an edge analytics appMonitor and audit edge analytics appsWho this book is for If you are a data analyst, data architect, or data scientist who is interested in learning and practicing advanced automated analytical computations, then this book is for you. You will also find this book useful if you’re looking to learn edge analytics from scratch. Basic knowledge of data analytics concepts is assumed to get the most out of this book.
Intelligent Workloads at the Edge
Author: Indraneel Mitra
language: en
Publisher: Packt Publishing Ltd
Release Date: 2022-01-14
Explore IoT, data analytics, and machine learning to solve cyber-physical problems using the latest capabilities of managed services such as AWS IoT Greengrass and Amazon SageMaker Key FeaturesAccelerate your next edge-focused product development with the power of AWS IoT GreengrassDevelop proficiency in architecting resilient solutions for the edge with proven best practicesHarness the power of analytics and machine learning for solving cyber-physical problemsBook Description The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs. This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You'll begin by discovering how to create software applications that run on edge devices with AWS IoT Greengrass. As you advance, you'll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to train these models and run them at the edge for optimized performance, cost savings, and data compliance. By the end of this IoT book, you'll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting. What you will learnBuild an end-to-end IoT solution from the edge to the cloudDesign and deploy multi-faceted intelligent solutions on the edgeProcess data at the edge through analytics and MLPackage and optimize models for the edge using Amazon SageMakerImplement MLOps and DevOps for operating an edge-based solutionOnboard and manage fleets of edge devices at scaleReview edge-based workloads against industry best practicesWho this book is for This book is for IoT architects and software engineers responsible for delivering analytical and machine learning–backed software solutions to the edge. AWS customers who want to learn and build IoT solutions will find this book useful. Intermediate-level experience with running Python software on Linux is required to make the most of this book.
Hands-On Industrial Internet of Things
Author: Giacomo Veneri
language: en
Publisher: Packt Publishing Ltd
Release Date: 2024-11-15
Build scalable, secure, and intelligent systems by utilizing IoT architectures, AWS, Azure, AI, and real-world solutions to become a skilled IIoT architect Key Features Leverage IoT, AI/ML, and cloud technologies to unlock industrial potential and drive business innovation Work with labs on real-world edge computing scenarios, integrating AWS, Azure, and open source tools Use diagnostic and predictive analytics to develop digital twins, improve industrial processes, and manage assets Purchase of the print or Kindle book includes a free PDF eBook Book Description In today's automation-driven era, precision is crucial, and the Industrial Internet of Things (IIoT) has made a remarkable impact. This updated second edition explores the technologies fueling the IIoT revolution and shares essential knowledge to enable you to establish remote-access networks. Written by IIoT and AI experts, as well as renowned authors, this book helps you enhance your skills in emerging technologies by introducing new techniques from Azure and AWS and keeping you up to date with the latest advancements. You'll find out how Artificial Intelligence of Things (AIoT) and MLOps apply to IIoT and learn how to handle complex projects confidently. The book covers identifying and connecting industrial data sources from various sensors, advancing from foundational concepts to professional skills. You'll discover how to connect these sensors to cloud networks such as AWS IoT, Azure IoT, and open source IoT platforms, and extract data from the cloud to your devices. Through hands-on experience with tools such as Node-RED, OPC UA, MQTT, NoSQL, defense in depth, and Python, you'll develop streaming and batch-based AI algorithms. By the end of this book, you'll have achieved a professional level of expertise in the cloud, IoT, and AI, and be able to build more robust, efficient, and reliable IoT infrastructure for your industry. What will you learn Get a solid understanding of industrial processes, devices, and protocols Harness IoT technology to effectively manage industrial use cases Design and implement an IIoT network flow to continuously monitor the performance of your critical assets Get to grips with popular cloud-based platforms such as AWS and Azure Explore Edge devices and learn about Edge and fog computing to gather field data Apply diagnostic analytics to real-world data to answer critical workforce questions Develop AIoT technology for predictive maintenance Who this book is for If you are an IoT architect, developer, AI engineer, or stakeholder involved in designing the architecture systems of the Industrial Internet of Things, this book is for you. The only prerequisite needed is a solid understanding of the Python programming language and networking concepts.