Building Digital Twin Checks for AI Service Requirements
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Solution Overview
Problem
Existing building systems struggle to determine which artificial intelligence solutions are appropriate for their specific configurations and equipment, leading to inefficiencies in implementing AI services.
Innovation Solution
A building system that utilizes a digital twin, such as a knowledge graph, to analyze requirements and determine if AI services can be implemented by checking if the system meets the necessary data elements and relationships, and if not, recommends equipment updates or data simulations to meet those requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a building system attempts to implement AI services without verifying requirements against its specific configuration, then AI service implementation may proceed quickly, but the system may lack necessary data elements and equipment, leading to service failure or inefficiency
Solution Approach 1:
The system performs preliminary requirement verification by comparing AI service requirements against the building's digital twin before implementation. This advance checking ensures all necessary data elements and equipment are present, preventing service failure while maintaining a manageable verification process through automated comparison logic.
Solution Approach 2:
A requirement verification module acts as an intermediary between AI service requests and the building system. This mediator compares service requirements against the digital twin, identifies gaps, and recommends equipment updates, thereby ensuring reliable AI service implementation without requiring complex direct integration between all system components.
2Adaptability or versatility
If the building system performs comprehensive requirement analysis before AI service implementation, then service compatibility is improved, but the time and computational resources required increase
Solution Approach 1:
The system uses a digital twin—a virtual copy of the building's physical assets, data elements, and configurations—to perform requirement verification. This copying approach allows comprehensive compatibility checking without requiring physical inspection or actual service deployment, significantly reducing verification time while maintaining high adaptability.
Solution Approach 2:
The requirement verification process focuses on checking only the specific data elements and equipment needed for the requested AI service, rather than performing a complete system-wide analysis. This partial action approach reduces computational overhead and verification time while ensuring sufficient service compatibility.
3Productivity
If the building system lacks certain data elements or equipment required for AI services, then implementing the service immediately is faster, but the service cannot function properly without the necessary components
Solution Approach 1:
The system performs preliminary checks to identify missing data elements or equipment before AI service deployment. By detecting gaps in advance, the system can either prepare the necessary components or adjust service selection, ensuring functional reliability while minimizing delays through targeted rather than comprehensive preparation.
Solution Approach 2:
The requirement verification module provides feedback about missing data elements or equipment to both the service selection process and the building owner. This feedback loop enables informed decisions about service deployment timing and priorities, balancing productivity goals with functional reliability requirements.
Data Source
AI summary
A building system can operate to receive a requirement to implement an artificial intelligence (AI) service. The requirement can include an indication of a type of an entity, wherein the AI service is configured to generate an analytic for the entity of the type of the entity or a control setting for the entity of the type of the entity. The requirement can include a data element that the AI service is configured to operate on to generate the analytic or the control setting. The building system can operate to determine that the building system meets the requirement to implement the AI service responsive to a determination that a digital twin of the building system includes the entity of the entity type and the data element and implement the AI service responsive to a determination that the building system meets the requirement.