Book Image

Analytics for the Internet of Things (IoT)

By : Andrew Minteer
5 (1)
Book Image

Analytics for the Internet of Things (IoT)

5 (1)
By: Andrew Minteer

Overview of this book

We start with the perplexing task of extracting value from huge amounts of barely intelligible data. The data takes a convoluted route just to be on the servers for analysis, but insights can emerge through visualization and statistical modeling techniques. You will learn to extract value from IoT big data using multiple analytic techniques. Next we review how IoT devices generate data and how the information travels over networks. You’ll get to know strategies to collect and store the data to optimize the potential for analytics, and strategies to handle data quality concerns. Cloud resources are a great match for IoT analytics, so Amazon Web Services, Microsoft Azure, and PTC ThingWorx are reviewed in detail next. Geospatial analytics is then introduced as a way to leverage location information. Combining IoT data with environmental data is also discussed as a way to enhance predictive capability. We’ll also review the economics of IoT analytics and you’ll discover ways to optimize business value. By the end of the book, you’ll know how to handle scale for both data storage and analytics, how Apache Spark can be leveraged to handle scalability, and how R and Python can be used for analytic modeling.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

IoT networking data messaging protocols


There are many strategies that IoT networked devices use to transfer data messages. Although connectivity and data messaging can sometimes blend together, we will discuss them separately for simplicity.

Not that it is really all that simple, but we will cover the most commonly used protocols. We will spend more time with the more frequently used ones.

Message Queue Telemetry Transport (MQTT)

MQTT is the most common data messaging protocol associated with IoT. It is supported by all the major cloud infrastructure providers (AWS, Microsoft, and Google). And it is most likely the protocol that is being used to deliver your data. It was designed for minimal power loss and minimal bandwidth requirements. It originated to support remote oil and gas use cases over satellite communication networks. It translated well into the broader IoT world as it developed in recent years.

 

At its heart, it is similar in concept to a messaging queue architecture but, despite...