Book Image

Enterprise Internet of Things Handbook

By : Arvind Ravulavaru
Book Image

Enterprise Internet of Things Handbook

By: Arvind Ravulavaru

Overview of this book

There is a lot of work that is being done in the IoT domain and according to Forbes the global IoT market will grow from $157B in 2016 to $457B by 2020. This is an amazing market both in terms technology advancement as well as money. In this book, we will be covering five popular IoT platforms, namely, AWS IoT, Microsoft Azure IoT, Google IoT Core, IBM Watson IoT, and Kaa IoT middleware. You are going to build solutions that will use a Raspberry Pi 3, a DHT11 Temperature and humidity sensor, and a dashboard to visualize the sensor data in real-time. Furthermore, you will also explore various components of each of the platforms that are needed to achieve the desired solution. Besides building solutions, you will look at how Machine Learning and IoT go hand in hand and later design a simple predictive web service based on this concept. By the end of this book, you will be in a position to implement an IoT strategy best-fit for your organization
Table of Contents (12 chapters)

Machine learning platforms

There was a time when people used to lease machines and set up data centers to run extensive machine learning algorithms and research. Thanks to the cloud, now all the cloud-based services are available on demand.

A data scientist can load a petabyte of data into a cloud server by running a bunch of algorithms on top of it, saving the data models, extracting the results, and deprovisioning the cloud resources, and will not be billed more than $50.

Isn't this a great time we live in?

Having said that, there are multiple platforms available on the market, some offered as cloud services, some proprietary, and some open source. In the following sections, I have listed a few of them in no particular order of preference.

Amazon machine learning