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Hands-On Edge Analytics with Azure IoT
By :
Hands-On Edge Analytics with Azure IoT
By:
Overview of this book
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.
Table of Contents (15 chapters)
Preface
Section 1: Getting Started with Edge Analytics
Free Chapter
Introduction to Edge Analytics
How Does IoT Edge Analytics Work?
Communications Protocols Used in Edge Analytics
Section 2: Understanding Edge Analytics Technologies
Working with Microsoft Azure IoT Hub
Using the Raspberry Pi with Azure IoT Edge
Using MicroPython for Edge Analytics
Machine Learning and Edge Analytics
Designing a Smart Doorbell with Visual Recognition
Section 3: The Road Ahead
Security and Privacy in an Edge Analytics World
What Next?
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