Hybrid Edge-Cloud BMS Control for Multi-Space Equipment Adaptation
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Solution Overview
Problem
Building management systems (BMS) often fail to account for various factors affecting space characteristics like temperature, humidity, and occupancy, leading to inefficient control of equipment such as HVAC systems, lighting, and security systems.
Innovation Solution
A method where an edge controller in a BMS receives data, analyzes it to determine if it satisfies certain conditions, and if not, requests cloud controller analysis using information from other spaces or domains, allowing for adaptive control of edge devices through neural networks and edge control adaptation commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all data analysis is performed by the edge controller using local information only, then the system operates independently and quickly, but the control precision and adaptability deteriorate due to inability to account for broader factors
Solution Approach 1:
The system divides control functions into two segments: edge controllers handle local real-time control using local information, while cloud controllers handle global optimization using comprehensive data from multiple sources. This segmentation allows each component to operate within its optimal capability range, improving overall control precision without requiring the edge controller to become overly complex.
Solution Approach 2:
The cloud controller acts as an intermediary between the edge controller and the building equipment. It receives local control requests, enriches them with additional contextual information from multiple spaces and domains, and returns optimized control commands. This intermediary approach enhances control precision by incorporating broader factors without increasing the complexity of the edge controller itself.
2Adaptability or versatility
If the edge controller requests cloud controller analysis for all data, then the adaptability and comprehensiveness of control improves, but the response time and operational efficiency deteriorate
Solution Approach 1:
The cloud controller performs preliminary analysis of data patterns and establishes optimization rules in advance. By pre-processing data and identifying common control scenarios, the system can quickly respond to routine situations using pre-computed strategies, reducing response time while maintaining adaptability for novel or complex situations that require real-time cloud analysis.
Solution Approach 2:
The system applies cloud controller analysis selectively rather than universally. Edge controllers request cloud analysis only when local information is insufficient or when complex decision-making is required. For routine control tasks, the edge controller operates independently using local information, thereby maintaining fast response times while still achieving high adaptability when needed.
3Productivity
If the system uses only local information for control decisions, then the operational speed is maintained, but the intelligence and comprehensive management capability deteriorate
Solution Approach 1:
The cloud controller serves multiple functions: it aggregates data from multiple spaces and building equipment domains, performs comprehensive analysis, generates optimization strategies, and distributes them to edge controllers. This multi-functional approach ensures that operational efficiency is maintained through local decision-making while information completeness is improved through centralized data aggregation and analysis.
Solution Approach 2:
The system implements a feedback mechanism where the cloud controller continuously receives data from edge controllers and building equipment, analyzes trends and patterns, and sends back optimization commands. This feedback loop ensures that operational efficiency is maintained through real-time local control while information completeness improves through continuous aggregation and analysis of comprehensive building-wide data.
Data Source
AI summary
A method includes receiving, by an edge controller, data relating to a first space. The edge controller controls operation of an edge device affecting a characteristic of the first space and that is associated with a first building equipment domain. The method further includes analyzing, by the edge controller, the data to determine whether the data satisfies a condition. If the condition is satisfied, the edge controller controls operation of the edge device using the data. If the condition is not satisfied, the edge controller (a) transmits a request to a cloud controller to analyze the data based on information obtained by the cloud controller regarding at least one of a second space or a second building equipment domain, (b) receives a response to the request from the cloud controller, and (c) controls operation of the edge device using the response from the cloud controller.