Semantic Labeling Analytics for Building Control System Optimization
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Solution Overview
Problem
Current building control systems lack the ability to effectively manage and optimize complex systems due to their model-free approach, which limits their capacity to translate digital models into human-readable formats, making it difficult to understand how computer actions correspond to human-understandable actions and hindering the creation of interconnected building zones and thermodynamic control optimization.
Innovation Solution
A system that uses semantic labeling analytics, where a controller translates device languages into a common internal language, creates actors based on device characteristics, and uses physics equations to simulate and report on building management system analytics, enabling human-readable reports and real-time monitoring of building systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a model-free approach is used in building control systems, then implementation is simple, but the system becomes difficult to manage and optimize as complexity increases
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the building system that mirrors the physical system's behavior and state. This digital model can be manipulated and analyzed without affecting the physical system, enabling complex simulations and optimizations while keeping the actual control system relatively simple to implement.
Solution Approach 2:
The digital twin serves as an intermediary between the physical building system and the control/optimization processes. It translates complex physical system behavior into a virtual representation that is easier to manage, analyze, and optimize, while maintaining accurate reflections of the physical system's state.
2Productivity
If a digital model is created for building systems, then control optimization is enabled, but translating the computer version into human-readable format becomes difficult
Solution Approach 1:
The digital twin acts as an intermediary layer between the complex computational models and human users. It maintains the full mathematical and thermodynamic complexity needed for optimization while presenting simplified, intuitive visualizations and interfaces that are easy for humans to understand and interact with.
Solution Approach 2:
The system provides different levels of detail and representation for different users and purposes. The digital model maintains full computational complexity for optimization algorithms while presenting simplified, context-specific views to human users based on their needs and expertise levels.
3Adaptability or versatility
If building systems integrate multiple interconnected subsystems, then system functionality increases, but complexity management becomes exponentially more difficult
Solution Approach 1:
The patent divides the complex building system into discrete, manageable components or zones within the digital twin. Each component can be independently modeled, analyzed, and optimized, while the digital twin maintains the interconnections and synergistic relationships between them, making the overall system manageable despite its complexity.
Data Source
AI summary
Tools and techniques are described to create an interface that can translate a device language into an internal language, and describe the device to the controller in terms of actors and quanta such that when a device is attached to a controller, the controller can understand what the device does and why it does it. This internal language can then be translated back to a natural language, such as English. This allows the controller to track errors, determine what upstream or downstream device and action of the device caused the error, and to track many different facts of the system that allow for detailed reports.