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Introduction to Edge Analytics

Everything old is new again! The rise of the personal computer (PC) in the 1980s and 1990s led to a revolution in computing. Instead of so-called dumb terminals connected to a large computer, many computers were connected in a network, spreading the processing power around. Edge analytics is like the personal computer revolution, but for IoT (Internet of Things) devices. We will start this chapter by comparing edge analytics to the computer revolution before we discuss the advantages of using edge analytics in an IoT application. We will look at the basic edge analytics architecture, as well as introduce the Microsoft Azure IoT Edge platform.

This chapter will cover the following topics:

What is edge analytics?
Applying and comparing architectures
Key benefits of edge analytics
Edge analytics architectures
Using edge analytics in the real world

Key benefits

Become well-versed with best practices for implementing automated analytical computations

Discover real-world examples to extend cloud intelligence

Develop your skills by understanding edge analytics and applying it to research activities

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.

Who is this book 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.

What you will learn

Discover the key concepts and architectures used with edge analytics

Understand how to use long-distance communication protocols for edge analytics

Deploy Microsoft Azure IoT Edge to a Raspberry Pi

Create Node-RED dashboards with MQTT and Text to Speech (TTS)

Use MicroPython for developing edge analytics apps

Explore various machine learning techniques and discover how machine learning is related to edge analytics

Use camera and vision recognition algorithms on the sensory side to design an edge analytics app

Monitor and audit edge analytics apps

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Kas Sep 07, 2020

Disclaimer: the publisher provided me a review copy of this book. The review below is my unbiased opinion and has not been edited or reviewed by the publisher.The book is a great resource for those starting their journey developing simple IoT applications, with or without Edge Computing. And since Edge Computing is one of the heavy IoT trends, it does not hurt starting the journey by focusing on those types of solutions. It is written in a very accessible language, chapters are short, and whenever necessary lots of details are provided, such as in the Hands On Lab scripts.I actually suggest the readers to review Chapters 1, 3, 4 and 7 first, then go back to the remaining chapters which give you examples and walk you through on the steps to build the elements of your Edge Analytic Solutions. And since spoilers are not a concern, it might be useful to read pages 223~225 first.What I liked:1) Chapters 2 and 3 do, in a short and sweet fashion, a great job of introducing the novice IoT developer to actual basic Edge components, such as common sensors and micro controllers, software code, connectivity options and lists examples of real life applications.2) The use of Device Explorer tool as an alternate way to connect to IoT Hub and monitor the output of the simulated devices.3) How thorough the Lab instructions are.4) The fact the author dedicated a good chapter to address security and privacy.What I did not like was mostly cosmetic:1) Quite some unnecessary information on Chapter 3 - pages 57~63 - could be left out or pushed to an appendix.2) Many questions at the end of each chapter do not add to the learning experience and I find hard to see the relevance to the topic (i.e. “What is the frequency used for CB channel 19 in Canada and the United States?”). The author should consider reducing the amount of questions and keep only relevant ones in future editions. And no matter how simple the questions are, it is a good practice to provide an answer key somewhere in the book.3) The Azure IoT Edge Components picture where one reads [Devices/Actions - IoT Edge/Decision - Azure IoT/Learning] could read instead [Devices/sensors and actuators - IoT Edge/data consumption and processing - Azure IoT/data storage, visualization and predictive analytics] which matches the approach used in chapter 6.What I missed:1) Pages 18-22 why not use a video analytics solution to compare architectures? I believe it would be easier to exemplify the advantages of an Edge Solution by comparing cost of all data traffic and storage, and delays, if all frames from all cameras are sent to the cloud for on-the-fly processing.2) Since the book covers the Solutions using Azure IoT technology, I missed information about Azure Sphere, maybe that topic is a bit too advanced for the intended book audience.

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Gerardo Reyes Ortiz Oct 06, 2020

Disclaimer: The publisher asked me to review this book and gave a review copy, I will be 100% honest in my review about the good. The review is my personal opinionOverviewThe book is for anyone who has interest in learning abput IoT and specially Microsoft IoT Platform. You dont require previous experience in IoT only some tech/computer background.What I like:This book is great if you really don't have a lot of knowledge about IoT or concepts like the "edge." I greatly enjoyed reading about the history of concepts so common today as well as the reasons why you should learn about IoT right now.The comparison between the different architectures was wonderful taking you by the hand to understand the differences and when to use one or the other.The way he first shows you all the concepts and then puts them together and makes them fit into the practical examples was great. In addition, the clear way in which it explains the examples facilitates understandingOne of the topics that is not usually covered is the different types of protocols, I loved that he mentioned and explained several of them since in the day to day it is usual that you use them.That I did not like:I would have liked to read something about Azure Sphere

Adwait Ullal Oct 19, 2020

Disclaimer: I was provided with a free copy of this book, but the below is my objective review of the bookThe book "Hands-On Edge Analytics with Azure IoT" is a good starter book for anyone interested in IoT.Especially, since it starts with the introduction on Edge Analytics, the components and devices that make up an Edge Analytics solution.Next, it discusses the various communication protocols suitable for an edge device to talk to the hub.It then delves into an introduction of Microsoft Azure and Azure IoT Hub and how devices can be provisioned within the environment. It uses the Raspberry Pi as an example.After the completed (hardware) system is connected to the IoT hub, it then discusses the use of MicroPython in the environment and how it helps in Edge Analytics.There is also a topic about Machine Learning and its role in Edge Analytics, which I suspect might be too advanced for the novice. As part of it, there is an exercise of designing a Smart Doorbell which uses the learnings so far.Finally, it discuss the Security and Privacy issues encountered in IoT and how to mitigate those.As I stated above, this is a good book for a novice who needs to understand IoT and Edge computing.

Hands-On Edge Analytics with Azure IoT: Design and develop IoT applications with edge analytical solutions including Azure IoT Edge

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Hands-On Edge Analytics with Azure IoT

Introduction to Edge Analytics

What is edge analytics?

Early computers

Applying and comparing architectures

The standard IoT solution

Key benefits of edge analytics

Edge analytics architectures

Basic edge analytics architecture

Using edge analytics in the real world

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