Digital Twin Object Tagging With AR Distance-Based Localization
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Solution Overview
Problem
Existing building information models are limited in their extensibility and require cumbersome tools for capturing and combining information, making it difficult for untrained users to create comprehensive digital twins for various applications.
Innovation Solution
An augmented reality method for scanning buildings into digital twins, enabling easy tagging and capturing information about real-world objects using a processor, camera, depth sensor, and user interface, allowing users to tag objects and store their locations and labels in the digital twin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional building information modeling tools are used to capture and combine building information, then comprehensive building data can be obtained, but the process becomes cumbersome and difficult for untrained users
Solution Approach 1:
The system creates a digital twin - a virtual copy of the physical building - that mirrors the real-world structure. By capturing spatial data through scanning and creating a digital replica, the system preserves complete building information while simplifying user interaction. Users work with the digital copy rather than manually compiling data, eliminating the cumbersome process of combining multiple diagrams while maintaining information completeness.
Solution Approach 2:
The patent replaces traditional mechanical/manual processes of building information capture (manually creating and combining diagrams) with automated scanning and processing systems. The system automatically captures spatial data, generates the digital twin, and populates building information without requiring users to manually assemble multiple diagrams, thus preserving information completeness while dramatically improving ease of operation.
2Adaptability or versatility
If detailed information about every building component is captured manually, then comprehensive digital models can be created, but the process becomes time-consuming and complex
Solution Approach 1:
The system performs preliminary scanning and data capture actions before the user needs the information. By pre-capturing spatial data, object locations, and building features through automated scanning, the system prepares the digital twin in advance. This eliminates the need for time-consuming manual data entry later while maintaining the ability to capture detailed information about every building component, thus improving adaptability without increasing time investment.
Solution Approach 2:
The system enables self-service building information capture where the scanning system automatically identifies and records building components, their locations, and relevant data without requiring manual intervention. The digital twin populates itself with comprehensive building information through automated processes, making the system highly adaptable and extensible while eliminating time-consuming manual data entry.
3Adaptability or versatility
If comprehensive object information is stored in the digital twin, then downstream applications can be enabled, but the system complexity increases
Solution Approach 1:
The digital twin serves as a universal platform that can support multiple downstream applications simultaneously. By creating a comprehensive yet standardized digital representation of the building with structured object information, the system enables diverse applications (facility management, security, maintenance, etc.) without increasing complexity for each individual application. The single digital twin structure provides multi-functional support, making the system adaptable while maintaining manageable complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables untrained users to easily create and maintain comprehensive digital twins, facilitating downstream applications such as object location, tracking, and augmented reality guidance.
Implementation Method 1
determining a distance from a location of the camera to a location of the object
Implementation Method 2
depth sensor
Data Source
AI summary
Various embodiments relate to a method, apparatus, and machine-readable storage medium including one or more of the following: receiving, from a user, a command to tag an object currently in view of a camera and located within a physical space; in response to the command, determining a distance from a location of the camera to a location of the object; determining the location of the object based on the determined distance; storing the location of the object and a label together as a tag in a digital twin representing the physical space; displaying a representation of the physical space; and displaying an indicator of the tag at a location in the representation of the physical space corresponding to the location of the object.