Building Graph Dashboards for Fast Energy Timeseries Visualization
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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 management of building energy data.
Innovation Solution
A building energy management system that includes a data collector, data platform services, and an energy management application, which processes raw data samples to generate optimized timeseries data and allows for the creation of ad hoc dashboards with interactive visualizations, enabling real-time data analysis and visualization.
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 into optimized data structures (such as time-series databases or columnar storage formats) at the time of data collection rather than leaving it raw. This preliminary organization enables faster query performance and data presentation without sacrificing storage simplicity, as the data is structured in an efficient format from the outset.
2Adaptability or versatility
If applications retrieve and process raw timeseries data in response to requests, then data processing flexibility is improved, but data presentation speed deteriorates
Solution Approach 1:
The system performs preliminary processing of timeseries data into optimized formats and pre-computes common aggregations and views. This allows applications to quickly retrieve pre-processed data with high presentation speed while maintaining flexibility through the ability to generate custom views and aggregations when needed.
Solution Approach 2:
The patent creates optimized copies of the raw timeseries data in different formats and levels of aggregation. These copies (such as summarized data, pre-aggregated time windows, or transformed views) enable fast data presentation while the original raw data remains available for flexible processing when required.
3Quantity of substance
If multiple timeseries are stored and processed for energy management, then data comprehensiveness is improved, but system complexity deteriorates
Solution Approach 1:
The patent implements a universal timeseries data platform that handles multiple timeseries data through a single standardized interface and storage system. This multi-functional approach allows comprehensive storage and processing of various building equipment data (HVAC, lighting, security, etc.) while reducing system complexity by avoiding separate specialized systems for each data type.
Solution Approach 2:
The system manages complexity by changing parameters such as data aggregation levels, time windows, and processing granularity. It can dynamically adjust these parameters based on query requirements, allowing comprehensive data analysis when needed while maintaining simplified views for routine monitoring, thus balancing comprehensiveness with manageable complexity.
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.