Building Management Resource Gap Detection for Smart Feature Upgrades
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Solution Overview
Problem
Building management systems face challenges in precisely identifying and responding to equipment needs due to variability across facilities and the lack of timely, precise data for service operations, making it difficult to determine required resources and implement additional features like smart building features.
Innovation Solution
A method using generative artificial intelligence (AI) models to scan building management systems, determine resource gaps, and generate proposals for updates, including configuration parameters, quotes, and maintenance actions, to enable smart building features by comparing available resources with feature requirements across multiple systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional building management systems are used without AI analysis, then system simplicity is maintained, but the ability to precisely identify resource needs and generate actionable service data deteriorates
Solution Approach 1:
The patent introduces an AI model as an intermediary component between the building management system and service operations. This intermediary processes raw building data, identifies resource needs, and generates actionable service data, thereby achieving precise resource identification without requiring direct complex processing in the core building management system.
Solution Approach 2:
The building management system performs self-assessment by automatically scanning its own resources and comparing them against feature requirements. The AI model enables the system to self-identify gaps and generate service proposals without external intervention, improving measurement precision while maintaining operational simplicity.
2Loss of information
If comprehensive scans of building management systems are performed to identify all resources, then completeness of resource data is improved, but the time and computational resources required deteriorate
Solution Approach 1:
The patent extracts only the essential resource identification functions from comprehensive system scans. The AI model selectively processes building data to identify specifically those resources relevant to service operations and feature implementation, eliminating unnecessary data collection while maintaining completeness of critical resource information.
Solution Approach 2:
The system performs preliminary scanning and resource identification using the AI model before service operations begin. This preliminary action pre-generates actionable service data and identifies resource gaps in advance, reducing the time required during actual service execution while maintaining complete resource documentation.
3Productivity
If AI models are used to generate detailed service proposals and updates, then quality of service data and actionable insights is improved, but computational resource requirements and system complexity deteriorate
Solution Approach 1:
The AI model generates service proposals and updates with appropriate detail levels based on specific needs. Rather than producing exhaustive documentation for all scenarios, the system applies partial action by generating only the necessary level of detail required for each service operation, improving productivity while managing computational resources effectively.
4Measurement precision
If the system compares available resources against feature requirements using AI, then accuracy of determining resource gaps is improved, but the complexity of data processing and analysis deteriorates
Solution Approach 1:
The AI model serves as an intermediary that handles the complex comparison and analysis between available resources and feature requirements. This intermediary performs the sophisticated data processing needed for accurate gap determination, while the core building management system remains relatively simple, achieving high measurement precision without proportionally increasing overall system complexity.
Data Source
AI summary
A method includes performing, by one or more processors, a scan of a building management system to determine an indication of available resources of the building management system, determining, by the one or more processors, by processing the indication of the available resources of the building management system using at least one generative artificial intelligence (AI) model, a difference between the available resources of the building management system and a requirements of a feature for the building management system, and performing, by the one or more processors, one or more actions according to the difference.