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Artificial Intelligence for IoT Cookbook

Artificial Intelligence for IoT Cookbook

By : Roshak
4.9 (10)
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Artificial Intelligence for IoT Cookbook

Artificial Intelligence for IoT Cookbook

4.9 (10)
By: 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)
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Getting ready

In this recipe, we are going to deploy Z-Spikes on a Raspberry Pi with a Sense HAT. The hardware itself is a fairly common development board and sensor setup for people learning about IoT. In fact, students can send their code to the International Space Station to be run on their Raspberry Pi and Sense HAT. If you do not have the equipment, there is an alternative code in the GitHub repository that simulates the device.

Once you have powered on your Raspberry Pi and attached your Sense HAT, you will need to install SciPy. In Python, you can usually install everything you need with pip, but in this case, you will need to install it through the Linux operating system. To do this, run the following commands in a terminal window:

sudo apt update
apt-cache show python3-scipy
sudo apt install -y python3-scipy

You will then need to pip install numpy, kafka, and sense_hat. You will also need to set up Kafka on a PC. There are instructions in Chapter 1, Setting up the IoT and...

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