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Organization and Storage of Building Data Streams

Jorge Ortiz. Organization and Storage of Building Data Streams. Building Energy Consumption. Consume 40% of energy in the US Consume 72% of electricity in the United States 30% of energy consumed in buildings is wasted Building built according to models

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Organization and Storage of Building Data Streams

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  1. Jorge Ortiz Organization and Storage of Building Data Streams

  2. Building Energy Consumption • Consume 40% of energy in the US • Consume 72% of electricity in the United States • 30% of energy consumed in buildings is wasted • Building built according to models • No benchmarks or operational performance metrics • No system validation • Buildings change over time which affects efficiency

  3. Overview • Making use of available information streams • Supervisory control and data acquisition (SCADA) data examination and integration • Organization, storage, and querying of SCADA data • Shorting-comings • Goals for monitoring and actuation system • Integrated Sensor Stream Storage System (IS4) architecture

  4. Making Use of Building Data • While continuing to build and deploy a dense monitoring fabric… • Use data from sensors already in the building • SCADA system often pre-installed • Acquired the data from facilities, dump into database, and query • Use data for visualization, modeling, etc.

  5. SCADA SystemsSupervisory Control and Data Acquisition + SODA4R787__ART + Data

  6. Problem With SCADA • No systematic data organization • Metadata embedded in UI and filenames • No easy to find context information • Incomplete data • Missing type descriptions, location information • Low data yield

  7. Capturing Building Layout Chiller Pump Zone Chiller Vent Vent Pump SF EF AHU

  8. Element Relationships System Chiller • Building • Systems • Spaces/Zones • Structural relationship • Sensors/Actuators • Inside systems • Inside zones/spaces • Types Space Pump Zone Chiller Vent Vent Pump SF EF AHU

  9. Element Schema

  10. Relevant Queries • List temperature sensors on 4th floor of Soda hall • SELECT id FROM zone_sensors WHERE building=‘Soda’ and floor=4 AND id LIKE ‘%ART’ • Get all temperature sensor data in the last day on the 4th floor of Soda • SELECT * FROM sensor_data WHERE id=[list of sensors] AND timestamp >= ’ 2009-12-16 00:00:00’ and timestamp<=now()

  11. Models and Visualization • Visualization and modeling based on historical data

  12. Active Management and Control • Real-time monitoring, control, and actuation • Goals • Analyze the data as it is collected • Pipe data feed to modeling and visualization software components • Use incoming data and model output for online decision-making and control • Models set context for data, data adjusts model • Actuation

  13. Storage System Design • Traditional data collection components

  14. Storage System Design

  15. Current State and Ongoing Work • Current State • Application API available • Data publishing system available • Ongoing work • Stream processing engine • Subscription manager • Open questions • Scalability • Publisher/subscriber management • Data management • How much data should be archived? • Security

  16. More information • http://webs.cs.berkeley.edu/building_schema • JSON building schema available • Application API specification available • Questions?

  17. Extra Slides

  18. Capturing Building Layout (JSON Schema Organization)

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