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)

Getting ready

In this recipe, we are going to create a simple Android Studio application and add machine learning code to it. For this, you will need to download and install Android Studio. From there, create a new project and follow these steps:

  1. Upon opening Android Studio, from the Start menu, select + Start a new Android Studio project:

  1. Then, you will need to select a UI template. In this recipe, we are going to select an empty activity:

  1. On the next screen, you will see a wizard that gives you the option to give the project a name and select a language for it. For this project, we will be selecting Java as our language:

  1. With that, a new project will open. Now, we need to import TensorFlow Lite into our project. To do this, go to the build.gradle (Module: app) section under Gradle Scripts:

  1. In the build.gradle JSON file under the dependencies section, add a reference to TensorFlow Lite (implementation 'org.tensorflow:tensorflow-lite:+'...