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Digital Twins for Software Engineers

Disclaimer

This book has been generated using chitragupta. Despite some potential for hallucination, the ideas communicated in this book are accurate. Please send your corrections and suggestions to prasad.talasila@gmail.com

Audience

Software engineers and programmers who need an overall working knowledge of digital twins so they can collaborate with modeling experts, business managers, and customers.

Demonstrator

The book will be written by using a plant, pot and pump demonstrator where the goal is to control the soil moisture in the pot. There is a pre-existing physical twin (system) demo setup that will be used in this book. The demo detials are available on GitHub. Also see hardware implementation and the firmware for Raspberry Pi-based firmware that samples sensors and controls the pumps to control soil moisture. The matching digital twin is not available yet. It needs to be constructed as a running example in this book along the way.

Part I — The Big Picture

So you can hold your own in the kickoff meeting.

  1. Why Anyone Pays for a Digital Twin: Value, Markets, and Real Deployments
  2. Twin, Shadow, Model, Simulation: What a Digital Twin Actually Is — and Isn't
  3. The Anatomy of a Twin: A Reference Architecture in Software Terms

Part II — Modeling and Simulation Literacy

Your interface to the modeling experts — enough to ask good questions, not to build models.

  1. Just Enough Modeling: Physics-Based, Data-Driven, and Hybrid Models
  2. Just Enough Simulation: State, Time, Solvers, and Co-Simulation
  3. Simulators: How Each Kind of Model Gets Solved
  4. Should You Trust the Twin? Calibration, Credibility, and V&V
  5. Where AI Fits: Machine Learning as a Model, a Service, and a Risk

Part III — Building the Twin

Your home turf — the deep part of the book.

  1. Connecting the Physical: Sensors, Protocols, and Streaming Data
  2. Data Engineering for Twins: Time Series, Context, and Provenance
  3. Twin Services: Visualization, Monitoring, Prediction, and Decision Support
  4. Platforms and Composability: Buying, Building, and Assembling from Parts
  5. Standards and Open Source: What Exists So You Don't Build It Twice
  6. Running Twins in Production: Deployment, Evolution, and the Twin's Own Lifecycle
  7. Twins at Scale: Ecosystems