Synthetic Building Data Control for HVAC Compliance Screening
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing control systems for building equipment lack the ability to predictively model and ensure compliance with regulations and certification standards, leading to potential operational inefficiencies and non-compliance.
Innovation Solution
A method and system that utilize a generative artificial intelligence model to generate building data, determine compliance with regulations and certification standards, and adjust the operation of building equipment accordingly, including filtering non-compliant data and fine-tuning the AI model for improved compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If building equipment is operated without compliance verification, then operational efficiency is maintained, but regulatory compliance cannot be ensured
Solution Approach 1:
The system performs compliance verification in advance by generating synthetic building data and evaluating it against regulatory standards before actual equipment operation. This preliminary assessment ensures compliance is established beforehand, avoiding the need for complex real-time monitoring and adjustment mechanisms during operation.
Solution Approach 2:
The system creates synthetic copies of building data that replicate real-world scenarios without requiring actual building operations. These synthetic datasets allow compliance evaluation to be performed on replicated conditions, eliminating the need for complex integrated monitoring systems that would otherwise be required to track actual operational compliance.
2Reliability
If synthetic building data is generated and verified for compliance, then compliance risk is reduced, but data processing time increases
Solution Approach 1:
Compliance verification is performed in advance using synthetic data generation and evaluation. By completing the compliance assessment before actual equipment operation begins, the system eliminates the need for time-consuming real-time verification during operational phases, thus reducing overall processing time while maintaining compliance assurance.
3Reliability
If building data is filtered to remove non-compliant portions, then compliance is improved, but data quality and completeness may deteriorate
Solution Approach 1:
The system extracts and removes only the specific non-compliant portions of building data while retaining the compliant portions. This selective extraction approach maintains the overall quality and completeness of the dataset by preserving valid data points, whereas removing entire datasets or large portions would degrade data quality. The filtering process targets only the problematic elements that violate compliance standards.
Data Source
AI summary
A method for controlling building equipment includes generating building data relating to conditions in a building space using a generative artificial intelligence model. The method also includes determining whether the building data correspond to conditions in the building space that comply with one or more regulations or certification standards. The method includes, in response to determining that the building data correspond to conditions in the building space that comply with the one or more regulations or certification standards, using the building data to operate building equipment that serve the building space.