Digital Twins in Action

Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book. A digital twin is a software-based replica of a physical system that can be used to operate, monitor, and maintain it remotely. Working together, IoT sensors, 3D visualizations, simulation algorithms, AI models, and even robotics give a digital twin an impressive degree of control. This virtual environment is perfect for testing ideas, exploring "what if" scenarios, and unlocking insights—all without making costly changes in reality. Author Greg Biegel has developed numerous industry-scale digital twin platforms from the ground up. In this book, he shares this unique experience with real-world insights about state of the art digital twins you can put into action today. There’s no niche academic theory—just a complete, practical introduction to every layer of the digital twin stack. Digital Twins in Action teaches you how to: Define clear business objectives for digital twins Create digital representations of physical systems Blend computer vision, OCR, and generative AI with 3D geometric models Stream IoT sensor data into a twin Represent real-world systems as knowledge graphs Machine learning and agentic AI for analysis and decision-making About the book Digital Twins in Action is a hands-on guide to ing and building effective digital twins. In it, you’ll build a home-scale digital twin from the ground up. You’ll start with a framework for gathering requirements to ensure that what you deliver is perfectly suited to your needs. You’ll then work through the complete project step by step—from setting up sensors, to handling hardware, to working with embedded software. By the time you’re finished, you’ll have a twin that can generate 3D models from your phone, extract insights from video and text with computer vision, and even employ an AI agent. Along the way, Greg will point out techniques you can use to scale up your small twin too. About the reader For software developers and machine learning engineers. Some knowledge of physical systems engineering is helpful but not required. About the author Greg Biegel has been building digital representations of physical systems for large organizations for over 20 years, including 6 years creating a state of the art industrial digital twin platform for a leading Australian energy producer. He holds Computer Science degrees from Rhodes University, South Africa and Trinity College, Dublin.