Book Image

Artificial Intelligence for IoT Cookbook

By : Michael Roshak
Book Image

Artificial Intelligence for IoT Cookbook

By: Michael Roshak

Overview of this book

Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users’ lives easier. With this AI cookbook, you’ll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications. Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You’ll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you’ll learn how to deploy models and improve their performance with ease. By the end of this book, you’ll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems.
Table of Contents (11 chapters)

To get the most out of this book

Readers should have a basic understanding of software development. This book uses the Python, C, Java languages. A basic understanding of how to install libraries and packages in these languages as well as basic coding concepts such as arrays and loops will be helpful. A few websites that can help you brush up on the basics of different languages are:

To get the most out of this book a basic understanding of machine learning principles will be beneficial. The hardware used in this book are off the shelf sensors and common IoT development kits and can be purchased from sites such as Adafruit.com and Amazon.com. Most of the code is portable across devices. Device code written in Python can be easily ported to a variety of microprocessors such as a Raspberry Pi, Nvidia Jetson, Lotte Panda, or sometimes even a PC. While code written in C can be ported to a variety of microcontrollers such as the ESP32, ESP8266, and Arduino. Code written in Java can be ported to any android device such as a tablet or phone. 

This book uses Databricks for some of the experiments. Databricks has a free version at https://community.cloud.databricks.com.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.