DigiLAB

DigiLAB

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Overview
Curriculum
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This course will guide you through the intricacies of creating, implementing, and optimizing digital twins, offering a comprehensive understanding of their architecture and applications. Whether you're an industry professional, a budding engineer, or simply curious about the digital transformation, this journey will equip you with the knowledge and skills to harness the power of digital replicas in various sectors. Dive in, and let's bring the virtual and real worlds closer together!

Curriculum

  • 7 Sections
  • 296 Lessons
  • 3 Quizzes
  • 0m Duration
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Project data and Resources access
2 Lessons
  1. 1. Project data access
  2. 2. Demo sites documentation
0. Introduction to Digital Twins
46 Lessons1 Quiz
  1. 0.- Introduction to Digital Twins
  2. 1. Introduction to the course
  3. 1.1. What do you know about Digital Twins?
  4. 2.1. On Digital Twins
  5. 2.2. Planning
  6. 2.2.1. Assessment of existing conditions
  7. 2.2.2. Determine objectives and qualities
  8. 2.2.3. Major levels of digital twins
  9. 2.3. Methodology
  10. 2.4. Standards and Regulations
  11. 2.5. Digital twin benefits: Use cases, roles, stages
  12. 2.5.1. Use cases
  13. 2.5.2. Roles
  14. 2.5.3. Use cases
  15. 2.6. Computer tools
  16. 2.7. Knowledge
  17. 3. Digital twin aspects
  18. 3.1. Building digital twin
  19. 3.2. Dynamic updating
  20. 3.3. VR/AR/XR
  21. 3.4. Smartization
  22. 4. Examples and exercises
  23. 4.1. Exercise Ii1: Getting familiar with the demo sites
  24. 4.2. Viewing demo sites geometry
  25. 4.2.1. Exercise Ai1: Viewing demo site buildings using IFC
  26. 4.2.2. Exercise Ai2: Viewing demo site buildings using Revit
  27. 4.3. Access to sensor data
  28. 4.3.1. Exercise Bi1: Accessing sensor data via ThingSpeak website
  29. 4.3.2. Exercise Bi2: Accessing sensor data via ThingSpeak API
  30. 4.4. Digital twin in game engine
  31. 4.4.1. Exercise Ci1 : Sensordata visualization tool
  32. 4.5. Smartization
  33. 4.5.1. Exercise Di1
  34. 5. Digital twins in an (information) security perspective
  35. 5.1. Introduction on information security for digital twins
  36. 5.2. The McCumber Cube, also termed CNSS security model
  37. 5.3. Combining information security with object security
  38. 5.4. General security aspects to consider when handling digital twins
  39. 5.5. Demo sites as security cases: The security aspects connected to the demo sites
  40. 6 Digital Twin Intro / Discussion questions
  41. 7. References
  42. 7.1. Text books
  43. 7.2. Articles
  44. 7.3. WEB sites
  45. 8. Terminology
  46. 8.1. Glossary
  47. 8.2. Abbreviations
1. Building Digital Twins
29 Lessons
  1. 1. Building Digital Twins
  2. 1. Learning Outcome
  3. 2. Planning
  4. 3. Data Capture
  5. 3.1. Intro
  6. 3.2. Photogrammetry
  7. 3.2.1. Physical Principles
  8. 3.2.2. Operating technology
  9. 3.3. Laser scanning
  10. 3.3.1. Physical Principles
  11. 3.3.2. Operating technology
  12. 3.3.2.1. Platforms for laser scanning
  13. 3.3.2.2. Target points /georeferencing
  14. 3.3.2.3. Scanner parameters
  15. 3.3.3. Practical application / Exercise
  16. 3.3.3.1. Exercise A3.1 Laser scanner simulation
  17. 4. 3D Modelling
  18. 4.1 What is 3D modelling and why is it needed?
  19. 4.2. Intro: Software
  20. 4.3 Import point Cloud
  21. 4.4. Building modelling
  22. 4.5. Rooms / Spaces
  23. 4.6. Model enrichment
  24. 4.7. Material parameter
  25. 5. Dataflow
  26. 5.1. Formats
  27. 5.2 Coordinate System
  28. 5.3 Export
  29. 6. Summary
2. Updating Digital Twins with dynamic data
34 Lessons1 Quiz
  1. 2. Updating Digital Twins with dynamic data
  2. 1. Learning outcome
  3. 2. Sensorization Planning
  4. 2.1. Basic principles of sensors
  5. 2.2. Types of sensors
  6. 2.2.1. Environmental sensors 
  7. 2.2.2. Motion and Proximity sensors
  8. 2.2.3. Optical and Imaging sensors
  9. 2.2.4. Sound and Vibration sensors
  10. 2.2.5. Chemical and Biometric sensors
  11. 2.3. How to select suitable sensors for each application
  12. 2.4. Check your knowledge about sensors
  13. 3. Programming sensors
  14. 3.1. Programming platforms: Arduino IDE
  15. 3.2. Basic principles of programming: Arduino
  16. 3.3. How to program sensors to capture relevant data
  17. 3.3.1. Libraries
  18. 3.3.2. Pin definition
  19. 3.3.3. Initialization
  20. 3.3.4. Serial communication
  21. 3.3.5. Reading sensor data
  22. 3.3.6. Error handling: common issues and troubleshooting
  23. 3.4. Exercise - Create your own Arduino project
  24. 3.5. Exercise - Use Wokwi platform to explore and create Arduino projects
  25. 4. IoT platforms
  26. 4.1. Intro
  27. 4.2. Thingspeak
  28. 4.2.1. Install and configure ThingSpeak
  29. 4.2.2. Devices configuration
  30. 4.2.3. Data visualization
  31. 4.3. Arduino Cloud
  32. 4.4. Exercise: Connect an Arduino device to Thingspeak and visualize the data
  33. 4.5. Understanding APIs
  34. 4.6. Accessing ThingSpeak API for data retrieval
  35. 5. Summary
3. Virtual training on Digital Twins
53 Lessons
  1. 3. Virtual training on Digital Twins
  2. 1. Learning outcome
  3. 2. Introduction to VR AR XR
  4. 3. Software tools
  5. 3.1. Game engines
  6. 3.2. BIM-model software
  7. 3.3. Point cloud softwares
  8. 3.3.1. Autodesk Recap
  9. 3.3.2. CloudCompare
  10. 3.3.3. MeshLab
  11. 3.3.4. Agisoft Metashape
  12. 3.4. 3D optimization software
  13. 3.4.1. Simplygon
  14. 3.4.2. Blender
  15. 3.5. VR Software
  16. 3.5.1. Meta Quest Link
  17. 3.5.2. SteamVR
  18. 4. Preparing models
  19. 4.2. Preparing BIM model
  20. 4.3. Optimizing the point cloud models
  21. 4.3.1. Limiting and segmenting areas with Autodesk Recap
  22. 4.3.2. Segmenting, cleaning and creating meshes with CloudCompare
  23. 4.3.2.1. Segmentation tools
  24. 4.3.2.2. Filters and subsampling
  25. 4.3.2.3. Normals and sensors
  26. 4.3.2.4. Meshing and surface reconstruction
  27. 4.3.3. Fixing and decimating the models and building textures with Agisoft Metashape
  28. 4.3.3.1. Closing holes
  29. 4.3.3.2. Smoothing and decimating the model
  30. 4.3.3.3. Building textures
  31. 4.3.4. Building textures and simplifying meshes with MeshLab
  32. 4.3.5. Simplifying the meshes with Simplygon
  33. 5. Import models 
  34. 5.1. Model preparation and normals
  35. 5.1.1. Normals in MeshLab
  36. 5.1.2. Normals in CloudCompare
  37. 5.1.3. Import models and check normals in Blender
  38. 5.2. Import process to the Game Engines
  39. 5.2.1. Unity
  40. 5.3. Displaying and updating the models
  41. 5.4. Collaboration: Speckle
  42. 6. VR/AR
  43. 6.1. Software and hardware
  44. 6.2. Interactivity and movement in VR
  45. 6.3. Assessing the models in VR
  46. 7. Virtual Training
  47. 7.1. Presentation of the models
  48. 7.2. Movement and interaction in VR
  49. 8. Exercises
  50. 8.1. VR Development environment with Unity and model importing
  51. 8.2. Create 3D model from the Point cloud file and import the resulting model to Unity
  52. 8.3. Show live sensor data in Unity engine
  53. 9. Summary
4. Smartization of Digital Twins
105 Lessons1 Quiz
  1. 4. Smartization of Digital Twins
  2. 1. Learning outcome
  3. 2. Smartization in Digital Twin
  4. 2.1. Digital Twin
  5. 2.2. Digital Twin vs BIM
  6. 2.3. From BIM to Digital Twin
  7. 2.4. Digital model, Digital Shaddow and Digital Twin
  8. 2.5. Smartization
  9. 2.6. Suggested Literature
  10. 2.7. Assignment
  11. 2.8. Demo Site Case study
  12. 2.8.1. Demo Sites
  13. 2.8.2. The Case: Evaluation of Indoor Environment
  14. 2.9. Data Storage, sharing and Analyze
  15. 3. Smartization with Revit and Dynamo
  16. 3.1. Introduction: Installation and getting started
  17. 3.2. Visual programming with Dynamo
  18. 3.2.1. Revit Terminology
  19. 3.2.2. Programming Terminology
  20. 3.2.3. Programming Logic
  21. 3.2.4. Programming Control Flow
  22. 3.3. Quantity Take-Off
  23. 3.3.1. Getting Started
  24. 3.3.2. Walls (Area)
  25. 3.3.3. Walls (Type and Heat Transfer Coefficient)
  26. 3.3.4. Building Envelope
  27. 3.3.5. Filtering
  28. 3.3.6. Export to Excel
  29. 3.3.7. Continue Export to Excel
  30. 3.3.8. Assignment
  31. 3.3.9. Summing up
  32. 3.4. Digital Twin
  33. 3.4.1. Setting-up Revit Model
  34. 3.4.2. Web-Request
  35. 3.4.3. Web-Request Exercise (solution)
  36. 3.4.4. Temperature (Storting Data)
  37. 3.4.5. Indoor Environment Quality (CEN 16798)
  38. 3.4.6. Categorization
  39. 3.4.7. Colouring Rooms
  40. 3.4.8. All Rooms
  41. 3.4.9. A New Solution
  42. 3.4.10. Changing Parameter from Dynamo
  43. 3.4.11. Boolean Switch
  44. 3.4.12. Summing up
  45. 3.4.13. Assignment
  46. 3.5. Learn more about Dynamo
  47. 4. Smartization and data visualization with Power BI
  48. 4.1. Getting started with Power BI
  49. 4.1.1. Language and User Interface
  50. 4.1.2. Raw Data from NTNU server
  51. 4.1.3. Sensors and Location
  52. 4.1.4. Power BI, Power Query, & Power Pivot
  53. 4.2. Temperature analysis
  54. 4.2.1.1 Getting data from WEB
  55. 4.2.2. Filtering the "Things" (Rooms/monitors)
  56. 4.2.3. Visualizing Data with Line Charts
  57. 4.2.4. External weather data 
  58. 4.2.5. Exploring Time-Based Temperature
  59. 4.2.6. Analyzing Temperature in 10-Minute and Hourly Buckets
  60. 4.2.7. Data Integration: Synchronizing Indoor and Outdoor Temperature
  61. 4.2.8. Importing Excel Files
  62. 4.2.9. Integrating Calendar Table
  63. 4.2.10. Fixing Datatype for Temperature
  64. 4.2.11. Creating a Time Table
  65. 4.2.12. Creating relation to weather station
  66. 4.2.13. Visualization and Report View
  67. 4.2.14. Assignment
  68. 4.3. Thermal Comfort Analysis
  69. 4.3.1. Averaged Hourly based Temperature Table
  70. 4.3.2. Thermal Comfort Categorization
  71. 4.3.3. Visualizing data with Bar Chart
  72. 4.3.4. Changing the Room monitor
  73. 4.3.5. Synchronized Filtering of Year, Month and Day
  74. 4.3.6. Week Slicer
  75. 4.3.7. Day of the Week Slicer
  76. 4.3.8. Time of the Day Slicer
  77. 4.3.9. Optimize the Visualization and New Features
  78. 4.3.10. Assignment
  79. 4.4. Illuminance and Pir_motion
  80. 4.4.1. Getting Data from WEB
  81. 4.4.2. Visualizing Illuminance with a Line Chart
  82. 4.4.3. Visualizing Pir Motion with Line Chart
  83. 4.4.4. Hourly Average Tables for Illumination and PIR_Motion
  84. 4.4.5. Merging Illumination and PIR_Motion Tables
  85. 4.4.6. Identifying hours with Inefficient Artificial Lighting
  86. 4.4.7. Quantifying Artificial Lighting Efficiency
  87. 4.4.8. Assignment
  88. 4.5. A Digital Twin?
  89. 5. Vizualization of Revit data in PowerBI
  90. 5.1. Introduction
  91. 5.2. What is speckle?
  92. 5.2.1. Create a speckle account
  93. 5.2.2. Revit speckle connector
  94. 5.3. What is Power BI?
  95. 5.3.1. Revit project as raw data
  96. 5.3.2. Installation of Speckle Visual
  97. 5.4. Tutorial: Data visualization
  98. 5.4.1. Export data from Revit to Speckle
  99. 5.4.2. Import data from Speckle
  100. 5.4.3. Transform data
  101. 5.4.4. Visualization of data
  102. 5.5. Tutorial: Visualization of room data
  103. 5.6. Tutorial visualization of categories
  104. 5.7. Vizualization of Revit data in PowerBI
  105. 5.8. References and links
  106. 6. Summary
Demo Sites Documentation
27 Lessons
  1. 1. Demo Site Spain - DSS
  2. 1.1. Sensors installed
  3. 1.2. Type of sensors
  4. 1.3. Location of the sensors
  5. 1.4. Administration of the sensors
  6. 1.5. Accessing ThingSpeak API
  7. 1.6. JSON Data Format
  8. 1.7. Key components in the JSON Response
  9. 1.8. Example of use
  10. 1.9. Additional resources
  11. 2. Demo Site Norway - DSN
  12. 2.1. Overview
  13. 2.2. BIM part
  14. 2.3. Sensor part
  15. 2.4. Location of the sensors
  16. 2.5. Arduino User Account
  17. 2.6. Arduino terminology handling devices and sensors
  18. 2.7. Connecting the Arduino devices to internet
  19. 2.8. Access to current reading of the sensors
  20. 3. Long time storage (LTS) of sensor data
  21. 3.1. Database
  22. 3.2. API
  23. 3.3. Data management and data harvesting
  24. 3.4. User interface
  25. 3.5. Access to services
  26. 3.6. Access details
  27. 3.7. References
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