BMS Timeseries Views With Pre-Aggregation for Fast Data Queries
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Solution Overview
Problem
Building management systems (BMS) face delays in data presentation due to the need for raw timeseries data to be retrieved and processed in response to requests, leading to inefficient data visualization and query times.
Innovation Solution
A BMS that includes a data collector to generate raw data timeseries, a timeseries processing engine to apply predefined workflows for processing and optimizing data, and a storage interface to store both raw and derived data in a timeseries database, allowing for pre-aggregation and efficient data retrieval.
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 at the time of data collection, then data storage simplicity is improved, but data presentation speed deteriorates due to processing delays at query time
Solution Approach 1:
The patent applies preliminary action by pre-processing and organizing timeseries data at the time of collection into time buckets with aggregated statistics (min, max, mean, sum, count) before storage. This eliminates the need for processing delays at query time, as the data is already organized and ready for rapid retrieval and presentation.
2Adaptability or versatility
If applications retrieve and generate views of timeseries data in response to requests, then data processing flexibility is improved, but data presentation responsiveness deteriorates
Solution Approach 1:
The system pre-generates multiple views of the timeseries data during data collection, organizing it into time buckets with pre-computed aggregated statistics. This preliminary organization enables applications to retrieve pre-processed data quickly while maintaining the flexibility to generate different views as needed.
Solution Approach 2:
The patent implements continuous data organization and aggregation as data is collected, maintaining ready-to-use organized data structures continuously rather than processing intermittently at query time. This ensures data is always in an optimized state for rapid retrieval and presentation.
3Measurement precision
If raw timeseries data is processed at query time, then data accuracy is improved, but query performance deteriorates
Solution Approach 1:
The patent pre-computes accurate aggregated statistics (minimum, maximum, mean, sum, count) for time buckets during data collection. This preliminary computation ensures data accuracy is maintained while eliminating query-time processing delays, thus improving query performance without sacrificing precision.
Data Source
AI summary
A building management system (BMS) includes building equipment configured to provide raw data samples of one or more data points in the BMS. The BMS further includes a data collector configured to collect raw data samples from the building equipment and generate one or more raw data timeseries comprising a plurality of the raw data samples. The BMS also includes a timeseries processing engine. The timeseries processing engine is configured to identify one or more timeseries processing workflows that apply to the raw data timeseries, each of the workflows comprising a predefined sequence of timeseries processing operation. The timeseries processing engine is further configured to process the raw data timeseries using the identified timeseries processing workflows to generate one or more derived data timeseries. The BMS further includes a timeseries storage interface configured to store the raw data timeseries and the derived data timeseries in a timeseries database.