Book Image

Hands-On Artificial Intelligence for IoT - Second Edition

By : Amita Kapoor
Book Image

Hands-On Artificial Intelligence for IoT - Second Edition

By: Amita Kapoor

Overview of this book

There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence.
Table of Contents (20 chapters)
Title Page
Copyright and Credits
Dedication
About Packt
Contributors
Preface
Index

Chapter 1. Principles and Foundations of IoT and AI

Congratulations on purchasing this book; it suggests that you're keenly interested in keeping yourself updated with the recent advancements in technology. This book deals with the three big trends in the current business scenario, Internet of Things (IoT), big data, and Artificial Intelligence (AI). The exponential growth of the number of devices connected to the internet, and the exponential volume of data created by them, necessitate the use of the analytical and predictive techniques of AI and deep learning (DL). This book specifically targets the third component, the various analytical and predictive methods or models available in the field of AI for the big data generated by IoT.

This chapter will briefly introduce you to these three trends and will expand on how they're interdependent. The data generated by IoT devices is uploaded to the cloud, hence you'll also be introduced to the various IoT cloud platforms and the data services they offer.

This chapter will cover the following points:

  • Knowing what's a thing is in IoT, what devices constitute things, what the different IoT platforms are, and what an IoT vertical is
  • Knowing what big data is and understanding how the amount of data generated by IoT lies in the range of big data
  • Understanding how and why AI can be useful for making sense of the voluminous data generated by IoT
  • With the help of an illustration, understanding how IoT, big data, and AI together can help us shape a better world
  • Learning about some of the tools needed to perform analysis