Chapter 1, Introduction to IoT, introduces you to the concept of the Internet of Things or IoT and talks about how it all started. This chapter also elaborates on the IoT market and what it would be for an enterprise. Once we understand the market, we will be looking at various building blocks of IoT.
Chapter 2, Applications of IoT, covers various applications that are possible in the IoT space. This chapter showcases two major domains, healthcare and industrial IoT, and how enterprises can easily expand their horizons and penetrate the IoT market.
Chapter 3, Getting Started with IoT Platforms, talks about what off-the-shelf IoT platforms are and how they reduce the time and effort needed for anyone to quickly build enterprise-grade IoT solutions. This chapter introduces you to the five platforms that we are going to work with in this book. We will also be setting up Raspberry Pi 3, along with ThingSpeak platform to build an end-to-end solution that showcases the platform idea in its simplest form.
Chapter 4, AWS IoT, explains how to use the AWS IoT service to build an end-to-end solution with Raspberry Pi 3 as our main hardware. We will explore concepts such as Things, shadows, and rules services. To create a real-time dashboard, we will be working with Elasticsearch and Kibana.
Chapter 5, Azure IoT, explains how to use the Azure IoT service to build an end-to-end solution with Raspberry Pi 3 as our main hardware. We will explore concepts such as the IoT Hub and device twins. In order to create a real-time dashboard, we will be working with Power BI and stream analytics job.
Chapter 6, Google Cloud IoT, explains how to use Google Cloud IoT Core service to build an end-to-end solution with Raspberry Pi 3 as our hardware. We will explore concepts such as device registry, topics, and Pub/Sub subscriptions. To create a real-time dashboard, we will be working with BigQuery and Google Data Studio.
Chapter 7, IBM Watson IoT, explains how to use Watson IoT platform to build an end-to-end solution with Raspberry Pi 3 as our main hardware. We will explore concepts such as device registry, topics, and Pub/Sub subscriptions. In order to create a real-time dashboard we will be working with Watson IoT platform boards by creating schemas.
Chapter 8, Kaa IoT, explains how to use the most popular open source Kaa IoT middleware to build an end-to-end solution with Raspberry Pi 3 as our hardware. We will explore concepts such as applications, appenders, and Kaa schemas. In order to create a real-time dashboard, we will be working with REST appenders and the ThingsBoard platform.
Chapter 9, IoT and Machine Learning, demonstrates the true capability of IoT through the power of machine learning. In this chapter, we will understand machine learning at a high level and, using Azure Machine Learning Studio, we will build a simple web service that will predict the chance of rain based on the temperature, and humidity.
Chapter 10, Platform Comparisons, concludes this book by comparing the five IoT platforms we have worked on, based on various parameters. This chapter also talks about various IoT architectural solutions that can be built using these platforms.