Building Equipment Control Using Synthetic Data Compliance Screening
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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
1Productivity
If building equipment is operated based on real-world building data, then operational efficiency is improved, but compliance with regulations and certification standards cannot be guaranteed
Solution Approach 1:
The patent uses synthetic building data generated by generative AI models as a copy or simulation of real-world building data. This synthetic data allows the system to train predictive models and test compliance scenarios without using actual operational data, thereby maintaining operational efficiency while ensuring compliance through simulated validation
Solution Approach 2:
The system performs compliance verification in advance by generating synthetic data that represents various compliance scenarios and using it to train predictive models before actual operation. This preliminary action ensures that compliance requirements are built into the operational framework beforehand, rather than checking compliance after operations have occurred
2Reliability
If compliance verification is performed on all building data, then compliance assurance is improved, but data processing time and system complexity increase
Solution Approach 1:
Instead of verifying compliance on actual building data which would be time-consuming, the system creates synthetic copies of building data that embed compliance information. These synthetic datasets allow for rapid compliance verification during model training without requiring exhaustive checking of real operational data
Solution Approach 2:
The generative AI model automatically generates synthetic building data that inherently reflects compliance requirements. The system self-services the compliance verification process by embedding compliance constraints into the data generation process itself, eliminating the need for separate, time-consuming verification steps
3Measurement precision
If synthetic building data is used to train predictive models, then compliance prediction capability is improved, but data accuracy and realism may deteriorate
Solution Approach 1:
The system uses feedback loops where synthetic building data is generated, used to train predictive models, and then the model predictions are evaluated against known compliance outcomes. This feedback mechanism continuously refines the generative AI model to produce more realistic synthetic data that maintains compliance prediction accuracy while improving data realism
Solution Approach 2:
The synthetic building data is constructed as a composite that combines statistically accurate representations of building operations with embedded compliance constraints. This composite approach allows the data to maintain mathematical precision for compliance prediction while incorporating realistic operational patterns through careful design of the generative model
Data Source
AI summary
A method for controlling building equipment includes generating synthetic building data including synthetic operating parameters for building equipment that operate to affect one or more conditions of a building space using a generative artificial intelligence model, determining whether the synthetic building data comply with one or more regulations or certification standards by comparing the synthetic operating parameters or a value derived from the synthetic operating parameters against a threshold set by the one or more regulations or certifications standards, and operating the building equipment to affect the one or more conditions of the building space using the synthetic operating parameters in response to determining that the synthetic building data comply with the one or more regulations or certification standards.