Building management system with distributed data storage and processing
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Solution Overview
Problem
Building management systems (BMS) face bandwidth and computing power challenges due to centralized data processing, which leads to increased costs and potential bottlenecks in data transmission and processing capabilities.
Innovation Solution
A distributed data processing system where a BMS controller subdivides processing requests into sub-requests and distributes them to device controllers responsible for storing and processing time-series data locally, allowing each controller to perform operations such as cleansing, filling, aggregation, and statistical analysis before sending results back to the central controller.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If centralized data processing is used where all sensor and actuator data is sent to the BMS controller, then data processing can be performed centrally, but the available bandwidth decreases and the BMS controller requires high computing power and large database storage
Solution Approach 1:
The patent segments the centralized processing architecture into distributed processing units at device controller level. Each device controller independently processes its local sensor and actuator data, dividing the monolithic processing task into smaller distributed tasks that reduce network bandwidth requirements and individual controller resource demands.
Solution Approach 2:
The patent introduces a new architectural dimension by implementing a hierarchical processing structure with multiple levels: device controllers performing local processing, building area network for data exchange, and building level controller for aggregate management. This multi-dimensional architecture resolves the resource bottleneck by distributing processing across spatial and functional dimensions.
2Ease of operation
If the BMS controller stores all sensor and actuator data locally and performs all processing functions itself, then data access is simplified, but the BMS controller requires high computing power and large database storage capacity
Solution Approach 1:
The patent segments the centralized database into distributed data repositories at each device controller. This segmentation maintains data accessibility by keeping data close to its source while reducing the burden on any single controller, as each controller manages only its local data subset.
Solution Approach 2:
The patent implements local quality by enabling each device controller to store and process its own data locally, giving each part of the system the capability to independently manage its data. This local autonomy simplifies data access for local operations while reducing the complexity and resource requirements of centralized storage.
3Productivity
If distributed data processing is implemented where device controllers process data locally, then bandwidth is conserved and processing capacity is enhanced, but system complexity increases with multiple processing nodes
Solution Approach 1:
The patent implements universality by designing device controllers with multi-functional capabilities that can perform both local data processing and network communication functions. This multi-functionality reduces overall system complexity by consolidating capabilities into standardised controllers rather than requiring specialised components for each function.
Solution Approach 2:
The patent implements feedback mechanisms where device controllers report processing status and data quality metrics to the building level controller, which provides aggregate management and coordination. This feedback loop enables automated system-wide optimization while maintaining local processing autonomy, managing complexity through standardized communication protocols.
Data Source
AI summary
A building management system (BMS) includes a plurality of devices controllers, a BMS database, and a BMS controller. The device controllers are configured to monitor and control one or more HVAC devices and to store and process time-series data associated with the HVAC devices. The BMS database is configured to store a master-index, the master-index identifying the time-series data stored by each of the device controllers. The BMS controller is configured to receive a processing request that requires the time-series data stored by one or more of the device controllers. The BMS controller is further configured to generate one or more processing sub-requests. The device controllers are further configured to handle the processing sub-requests and provide processing results to the BMS controller. The BMS controller is further configured to combine processing results from the device controllers.