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Analytics for the Internet of Things (IoT)
Analytics for the Internet of Things (IoT)

Analytics for the Internet of Things (IoT): Intelligent analytics for your intelligent devices

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Analytics for the Internet of Things (IoT)

IoT Devices and Networking Protocols

You have started your analysis and found that your IoT data is not always complete. You also suspect it is not always accurate. But you have no idea why that would be the case. You get several hundred records a day on average from each device.

The IoT devices your company makes are attached to freight trailers and track location, and sometimes even temperature. The temperature is monitored when the trailer is a refrigerated unit, called a reefer in the industry. The inside temperature of a reefer must be kept in a certain range depending on what is being transported.

Your device is located on the outside of the trailer with a lead line into the trailer to read temperature if the option is enabled. The trailer is pulled around by big rig trucks over roads all over the country.

You have been so focused on finding value in the data, you never...

IoT devices

There is a wide variety of IoT devices in use today. The range of designs and ingenuity in function is expanding at a furious pace. The scope of what is being measured, monitored, and tracked would be an entire book in itself. And it is, as you can find several through the publisher of this book.

The wild world of IoT devices

For analytics purposes, it is helpful to understand the variety of devices and how they are being used. Ideas from one industry can cross-pollinate into another and create unexpected value. The combination of devices and use cases can also present very different analytics opportunities and challenges.

...

Networking basics

Here is an oversimplified view of the networking protocol stack. There is much more going on here than we will cover in this chapter, but to help in understanding the discussion, it is useful to reduce it to a simple diagram:

 

Network communications operates in layers with the bottom layers not needing to know about the layers above it. It can get confusing talking about all the options available at each layer of the stack. The diagram shows the key layers that we are concerned with for IoT analytics, but know that there is more to the story.

The diagram is based on the simplified OSI model, which divides communication into five fundamental layers. There is a Physical layer at bottom that has more to do with device electrical engineering. We will leave that out to simplify things since we are focusing on analytics.

Connectivity will refer to options primarily...

IoT networking connectivity protocols

Connectivity is all about solving the main problem - establishing a method to communicate. The strategies used are affected by the constraints on the network devices. Power availability often is the most significant one.

Connectivity protocols (when the available power is limited)

The following protocols are specifically designed to address low power constraints. They are usually associated with lower complexity and bit transfer rates in the supported IoT devices.

Bluetooth Low Energy (also called Bluetooth Smart)

Named after a tenth...

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...

Analyzing data to infer protocol and device characteristics

Back to the number-one rule in IoT analytics: Never trust data you don't know.

You need to get to know your data. Just like that new guy you just met, you Google him, ask around about him, and do a criminal background check (we know you do) before agreeing to go to dinner with him.

Here is a step-by-step strategy to start to understand the source of the data:

  1. Draw a picture of the device: Sketch it out or use blueprints if you have them. This is where you make friends with the design engineer and ask her some questions. Draw the key sensors in the place they are located and note the sensor type and any limitations. Ask about any environmental conditions that affect accuracy and note it.
  2. Find out how the device connects to a network: Note the connectivity type on your sketch.
  3. Determine what data messaging protocol...

IoT devices


There is a wide variety of IoT devices in use today. The range of designs and ingenuity in function is expanding at a furious pace. The scope of what is being measured, monitored, and tracked would be an entire book in itself. And it is, as you can find several through the publisher of this book.

The wild world of IoT devices

For analytics purposes, it is helpful to understand the variety of devices and how they are being used. Ideas from one industry can cross-pollinate into another and create unexpected value. The combination of devices and use cases can also present very different analytics opportunities and challenges.

Healthcare

Patients in acute care are having their vital signs monitored by low-power wireless sensors where the data can be analyzed remotely. There are several startups, such as Proteus Digital Health, that are developing pill-sized ingestible sensors. Proteus makes a digestible sensor pill that, in combination with a sensor patch worn on skin, monitors when...

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Key benefits

  • •Make better business decisions and acquire greater control of your IoT infrastructure
  • •Learn techniques to solve unique problems associated with IoT and examine and analyze data from your IoT devices
  • •Uncover the business potential generated by data from IoT devices and bring down business costs

Description

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.

Who is this book for?

This book targets developers, IoT professionals, and those in the field of data science who are trying to solve business problems through IoT devices and would like to analyze IoT data. IoT enthusiasts, managers, and entrepreneurs who would like to make the most of IoT will find this equally useful. A prior knowledge of IoT would be helpful but is not necessary. Some prior programming experience would be useful

What you will learn

  • •Overcome the challenges IoT data brings to analytics
  • •Understand the variety of transmission protocols for IoT along with their strengths and weaknesses
  • •Learn how data flows from the IoT device to the final data set
  • •Develop techniques to wring value from IoT data
  • •Apply geospatial analytics to IoT data
  • •Use machine learning as a predictive method on IoT data
  • •Implement best strategies to get the most from IoT analytics
  • •Master the economics of IoT analytics in order to optimize business value

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 24, 2017
Length: 378 pages
Edition : 1st
Language : English
ISBN-13 : 9781787120730
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Product Details

Publication date : Jul 24, 2017
Length: 378 pages
Edition : 1st
Language : English
ISBN-13 : 9781787120730
Category :
Languages :

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Table of Contents

13 Chapters
Defining IoT Analytics and Challenges Chevron down icon Chevron up icon
IoT Devices and Networking Protocols Chevron down icon Chevron up icon
IoT Analytics for the Cloud Chevron down icon Chevron up icon
Creating an AWS Cloud Analytics Environment Chevron down icon Chevron up icon
Collecting All That Data - Strategies and Techniques Chevron down icon Chevron up icon
Getting to Know Your Data - Exploring IoT Data Chevron down icon Chevron up icon
Decorating Your Data - Adding External Datasets to Innovate Chevron down icon Chevron up icon
Communicating with Others - Visualization and Dashboarding Chevron down icon Chevron up icon
Applying Geospatial Analytics to IoT Data Chevron down icon Chevron up icon
Data Science for IoT Analytics Chevron down icon Chevron up icon
Strategies to Organize Data for Analytics Chevron down icon Chevron up icon
The Economics of IoT Analytics Chevron down icon Chevron up icon
Bringing It All Together Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7
(6 Ratings)
5 star 83.3%
4 star 0%
3 star 16.7%
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1 star 0%
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Jesse H. Scott Sep 26, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Well written and thorough coverage of technology, hardware, software and how it is used. Good introductory material.
Amazon Verified review Amazon
f. e. nar Oct 13, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good book to expand your view with supplemental tools (not clear & useful how-to(s) btw), methodologies and even external datasets to get more out of your IoT solution/product, plus a happy ending career of a data analyst :-)
Amazon Verified review Amazon
Tony Dec 19, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a great book. It covers such a wide variety of topics in a clear and concise fashion. The author could have easily got lost in the detail given they were trying to cover a lot of ground - devices, networking, cloud, big data, visualisation, data science, deep learning, economics - but they managed to keep it at level that was useful and insightful. Being myself a veteran in the Analytics field, I could see how he managed to bring some very complex topics up and make the overall concept simple to understand. Some of his explanations around Big Data, cloud and analytics could be used independently of whether someone is interested in IoT or not.He even used a lot of humour throughout the book which is not very common amongst textbooks these days. Although I wish it was.If people want to get a high level overview of the spectrum from devices to analytics, I highly recommend this book. It is enough then to be the springboard into other areas of your choosing if you want more detail.I got the kindle version and it was well formatted and easy to read and came with a separate attachment with the images.
Amazon Verified review Amazon
Mugdha Hota Oct 18, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good
Amazon Verified review Amazon
Carlos Monge Perry Feb 21, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good book, clear and academic oriented.
Amazon Verified review Amazon
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