Building Graph Configuration for Faster Digital Twin Commissioning
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Solution Overview
Problem
The initial commissioning of new buildings and spaces within building management systems is time-intensive and costly, requiring significant manual effort and involving challenges in generating accurate digital representations of physical assets and spaces.
Innovation Solution
A smart configuration and commissioning system that automates the process of generating digital representations of buildings by ingesting and interpreting external data sources, extracting semantic information, and dynamically configuring building equipment, reducing the need for manual intervention and lowering the time and expense associated with commissioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual commissioning processes are used to generate digital representations of building assets, then accuracy of digital models can be maintained through human verification, but time consumption and expense increase significantly
Solution Approach 1:
The patent uses automated copying of building asset data from multiple sources (BIM models, device telemetry, operational data) to generate digital representations. Instead of manual creation, the system automatically copies and integrates data from various sources to populate the digital twin, significantly reducing time while maintaining accuracy through multi-source verification
Solution Approach 2:
The system implements feedback mechanisms where operational data from building devices continuously validates and updates the digital model. Sensors and devices provide real-time feedback that confirms the accuracy of digital representations, allowing automated generation while maintaining verification through ongoing data comparison
2Reliability
If comprehensive data validation and formatting processes are implemented to ensure data quality, then reliability of building models improves, but processing time and system complexity increase
Solution Approach 1:
The patent applies preliminary action by implementing data validation, formatting, and enrichment processes before data is integrated into the building model. Data is cleaned and standardized in advance using predefined schemas and validation rules, ensuring reliability is established upfront rather than through complex ongoing verification systems
Solution Approach 2:
The system changes parameters of incoming data by transforming various data formats into a standardized building model schema. Data undergoes parameter changes including type conversion, validation against schemas, and enrichment with additional information, simplifying the integration process while ensuring data quality
3Loss of information
If multiple data sources and formats are integrated to create comprehensive building models, then completeness of digital representations improves, but difficulty of data processing and format compatibility increases
Solution Approach 1:
The patent implements universality by creating a standardized building model schema that can accommodate multiple data sources and formats. The system uses a universal data structure (such as Brick Schema or similar building information models) that can represent various asset types and data formats uniformly, simplifying integration while maintaining completeness
Solution Approach 2:
The system uses an intermediary layer (data validation and transformation module) that mediates between diverse data sources and the final building model. This intermediary handles format conversion, validation, and standardization, allowing comprehensive data integration without directly managing the complexity of multiple formats throughout the entire system
Data Source
AI summary
A method for generating a graph data structure comprises receiving, by one or more processors, data associated with a building, generating one or more space nodes in the graph data structure corresponding to spaces within the building based on the data, generating one or more asset nodes in the graph data structure corresponding to assets within the building based on the data, associating sensor data with the one or more asset nodes based on the data, classifying the sensor data based on the data, and generating a relationship between at least two of the one or more space nodes, the one or more asset nodes, and the classified sensor data.