Building Alarm Classification Using AI Scenario Simulation
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Solution Overview
Problem
Building management systems frequently generate false alarms, diverting operator attention and resources away from actual issues, and existing methods lack effective automated means to distinguish between true and false alarms.
Innovation Solution
A system utilizing generative and discriminator AI models, along with domain knowledge, simulates scenarios to classify alarms as true or false based on sensor values and component states, removing dependent, trailing, and duplicate alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the Building Management System monitors all sensors and components continuously, then the system can detect actual issues promptly, but it generates numerous false alarms that divert operator attention and waste time
Solution Approach 1:
The patent introduces an intermediary AI-based classification system between the BMS sensors and the operator. This intermediary automatically analyzes alarm data using machine learning models to determine whether an alarm is true or false before presenting it to the operator, thereby filtering out false alarms and reducing unnecessary operator responses while maintaining timely detection of actual issues
Solution Approach 2:
The system performs self-service by automatically classifying alarms using AI models without requiring operator intervention for each alarm. The machine learning system independently analyzes sensor data, historical patterns, and contextual information to autonomously determine alarm validity, freeing operators to focus only on genuine issues
2Measurement precision
If the Building Management System uses traditional alarm monitoring methods, then the system structure remains simple, but it cannot effectively distinguish between true and false alarms
Solution Approach 1:
The patent replaces traditional mechanical/simple alarm monitoring mechanisms with an AI-based classification system. Machine learning models process alarm data by analyzing patterns, sensor relationships, and contextual factors to accurately classify true versus false alarms, providing precise measurement capability while accepting increased system complexity as necessary for improved performance
Solution Approach 2:
The system changes the parameters of alarm analysis by incorporating multiple dimensions of data including historical alarm patterns, sensor relationships, environmental context, and temporal patterns. This multi-parameter analysis enables precise alarm classification by considering numerous factors simultaneously rather than relying on simple single-parameter thresholds
3Productivity
If operators respond to every alarm individually, then each alarm receives attention, but operator productivity decreases due to time consumption on false alarms
Solution Approach 1:
The patent extracts false alarms from the total alarm stream using AI classification. The system separates and removes false alarms from the list of alarms requiring operator attention, extracting only the subset of true alarms that need human response. This extraction process increases operator productivity by reducing the quantity of alarms they must process while maintaining focus on genuine issues
Data Source
AI summary
False alarms may be mitigated in a Building Management System (BMS). Domain knowledge is received, as are a plurality of alarms. Some alarms are removed based at least in part on the domain knowledge, resulting in a shortlist of potential false alarms. A generative Artificial Intelligence (AI) model is applied to these alarms, simulating a virtual scenario for each alarm while considering the respective alarm as a true alarm. A discriminator AI Model is applied to determine whether the simulated virtual scenario for each alarm is probable or not. When the simulated virtual scenario is determined to be not probable, the respective alarm is classified as a false alarm and when the simulated virtual scenario is determined to be probable, the respective alarm is classified as a true alarm.