Building management system with artificial intelligence for unified agent based control of building subsystems
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Solution Overview
Problem
Current building management systems (BMS) lack a unified, intelligent framework to dynamically react to changing situational data across disparate building systems, leading to inefficiencies and potential safety issues due to predefined scripted operations.
Innovation Solution
A BMS with artificial intelligence capabilities, incorporating data collectors, a learning engine, and cognitive agents that correlate data streams from various subsystems to identify building states and generate control decisions, enabling dynamic and adaptive control of building conditions, including emergency responses like fire management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a unified AI-driven control framework is implemented, then building safety and operational efficiency are improved, but device complexity increases
Solution Approach 1:
The system segments building control into multiple cognitive agents, each responsible for specific building subsystems (HVAC, lighting, security, fire safety). Each agent independently processes data streams and makes control decisions for its designated subsystem, dividing the complex unified control task into manageable specialized components that collectively improve building safety without overwhelming system complexity
Solution Approach 2:
The cognitive agents serve multiple functions: they monitor building conditions, analyze data streams, generate control decisions, and execute operations across different building subsystems. This multi-functionality allows a single AI-driven framework to handle diverse building management tasks, improving overall system reliability while avoiding the need for separate specialized systems for each function
2Productivity
If cognitive agents autonomously generate control decisions, then productivity and responsiveness are improved, but loss of information increases
Solution Approach 1:
The system continuously receives data streams from building subsystems and feeds this information back to cognitive agents for real-time analysis and control decision generation. This closed-loop feedback mechanism ensures that autonomous agents base their decisions on current building conditions, maintaining information accuracy while enabling rapid autonomous responses that improve operational efficiency
Solution Approach 2:
The cognitive agents act as intermediaries between raw data streams from building subsystems and control operations. They process and interpret data, transforming raw information into meaningful control decisions, thereby preventing information loss while enabling autonomous productivity improvements
3Adaptability or versatility
If multiple data streams are correlated to identify building states, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system segments data stream processing by assigning specific data streams to cognitive agents based on their functional expertise. Each agent correlates only the data streams relevant to its subsystem, reducing individual processing complexity while collectively achieving comprehensive adaptability across all building systems through specialized division of data analysis tasks
Data Source
AI summary
A building management system with artificial intelligence based control of a building includes data collectors are configured to receive data and generate data streams for subsystems of the building. The system includes a learning engine configured to identify a building state of the building by correlating data of the data streams for the subsystems and provide the identified building state to cognitive agents. The system includes the cognitive agents, each of the cognitive agents configured to receive the identified building state from the learning engine, generate a control decision based on the received building state, and operate at least one of the plurality of subsystems of the building to control a physical condition of the building based on the control decision.