Book Image

Industrial IoT for Architects and Engineers

By : Joey Bernal, Bharath Sridhar
Book Image

Industrial IoT for Architects and Engineers

By: Joey Bernal, Bharath Sridhar

Overview of this book

When it comes to using the core and managed services available on AWS for making decisions about architectural environments for an enterprise, there are as many challenges as there are advantages. This Industrial IoT book follows the journey of data from the shop floor to the boardroom, identifying goals and aiding in strong architectural decision-making. You’ll begin from the ground up, analyzing environment needs and understanding what is required from the captured data, applying industry standards and conventions throughout the process. This will help you realize why digital integration is crucial and how to approach an Industrial IoT project from a holistic perspective. As you advance, you’ll delve into the operational technology realm and consider integration patterns with common industrial protocols for data gathering and analysis with direct connectivity to data through sensors or systems. The book will equip you with the essentials for designing industrial IoT architectures while also covering intelligence at the edge and creating a greater awareness of the role of machine learning and artificial intelligence in overcoming architectural challenges. By the end of this book, you’ll be ready to apply IoT directly to the industry while adapting the concepts covered to implement AWS IoT technologies.
Table of Contents (19 chapters)
1
Part 1:An Introduction to Industrial IoT and Moving Toward Industry 4.0
6
Part 2: IoT Integration for Industrial Protocols and Systems
11
Part 3:Building Scalable, Robust, and Secure Solutions

Advanced Analytics and Machine Learning

Hopefully, if you have gotten to this point on your journey, you are excited about the possibilities of getting started. Getting to this point has been a workout, but our ultimate goal is to thoroughly understand the how and why of good architectural decision-making. Machine Learning (ML) and Artificial Intelligence (AI) is an exciting topic that is still relatively new in our industry. Performing inference on data in real time to determine a course of action is powerful. Performing inference on your data is often a phrase you will hear in ML. It is the act of reaching a conclusion based on evidence and reasoning. In our case, we will look at how to infer a result or condition based on previous or existing data.

The authors of this book are not data scientists. Generally, we are IoT and cloud architects with a broad set of skills focused on the topics needed to deliver a complex IoT solution, including experience in data collection, engineering...