Building Graph Dashboards for Faster Timeseries Retrieval
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Solution Overview
Problem
Building management systems (BMS) face delays in data presentation due to the storage of raw timeseries data in relational databases without significant organization or processing, leading to inefficient data retrieval and visualization.
Innovation Solution
A building energy management system with a data collector, data platform services, and a timeseries database that generates optimized data timeseries and ad hoc dashboards for interactive visualization, including widgets for data rollup, virtual points, and analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If raw timeseries data is stored in a relational database without significant organization or processing, then data storage simplicity is improved, but data retrieval efficiency deteriorates
Solution Approach 1:
The patent pre-processes and organizes raw timeseries data into structured formats with metadata, tags, and relationships before storage. This preliminary organization enables efficient querying and retrieval without requiring complex processing at query time, thus resolving the contradiction between storage simplicity and retrieval efficiency.
Solution Approach 2:
The patent segments timeseries data into organized collections with metadata, tags, and hierarchical relationships. By dividing raw data into structured components with meaningful organization, the system enables efficient retrieval while maintaining storage simplicity through modular architecture.
2Adaptability or versatility
If applications retrieve and process raw timeseries data in response to requests, then data processing flexibility is improved, but data presentation time deteriorates
Solution Approach 1:
The patent performs preliminary processing of timeseries data during ingestion, organizing it into structured collections with metadata, tags, and relationships. This pre-processing enables applications to quickly retrieve and visualize data without performing complex processing at query time, thus reducing data presentation time while maintaining processing flexibility.
Solution Approach 2:
The patent introduces an intermediary data layer between raw data collection and application processing. This intermediary layer pre-organizes data with metadata and relationships, serving as a mediator that enables both flexible application processing and fast data presentation by reducing the processing burden at query time.
3Device complexity
If timeseries data is stored without significant organization, then storage complexity is reduced, but data analysis capability deteriorates
Solution Approach 1:
The patent segments timeseries data into organized collections with metadata, tags, and hierarchical relationships. This segmentation enables rich data analysis capabilities by preserving contextual information and relationships while maintaining manageable storage complexity through modular organization.
Solution Approach 2:
The patent performs preliminary organization of data with metadata and relationships during the ingestion phase. This preliminary action preserves analytical information and contextual relationships without significantly increasing storage complexity, as the organization is implemented through efficient data structures and indexing mechanisms.
Data Source
AI summary
A building energy management includes building equipment, one or more data platform services, a timeseries database, and an energy management application. The building equipment operate to monitor and control a variable and provide raw data samples of a data point associated with the variable. The timeseries database stores a plurality of timeseries associated with the data point. The plurality of timeseries include a timeseries of the raw data samples and the one or more optimized data timeseries generated by the data platform services based on the raw data timeseries. The energy management application generates an ad hoc dashboard including a widget and associates the widget with the data point. The widget displays a graphical visualization of the plurality of timeseries associated with the data point and includes interactive user interface options for switching between the plurality of timeseries associated with the data point.