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)

Manifold 2-C with NVIDIA TX2

The NVIDIA Jetson is one of the best choices for running complex ML models such as real-time video on the Edge. The NVIDIA Jetson comes with a built-in NVIDIA GPU. The Manifold version of the product is designed to fit onto a DJI drone and perform tasks such as image recognition or self-flying. The only downside to running NVIDIA Jetson is its use of the ARM64 architecture. ARM64 does not work well with TensorFlow, although other libraries such as PyTorch work fine on ARM64. The Manifold retails for $500, which makes it a high-price option, but this is often necessary when doing real-time ML on the Edge:

Price Typical Models Use Cases
$500 Re-enforcement learning, computer vision Self-flying drones, robotics