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Infrastructure Services for Physical Data Stephen Dawson-Haggerty.

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Presentation on theme: "Infrastructure Services for Physical Data Stephen Dawson-Haggerty."— Presentation transcript:

1 Infrastructure Services for Physical Data Stephen Dawson-Haggerty

2 Cyber / Physical Building BMS Cyber PhysicalBuilding Light Transport Process Loads Occupant Demand Legacy Instrumentation & Control Interfaces Pervasive Sensing Activity/Usage Streams BIM PIB Activity Models Multi-Objective Model- Driven Control Building Integrated Operating System External HVAC Electrical Fault, Attack, Anomaly Detect &Management Control Plan and Schedule Physical Models Human-Building Interface

3 Open Platform for Building Applications 3

4 Internet Cell phone sMAP Gateway sMAP Modbus RS-485 sMAP sMAP Gateway EBHTTP / IPv6 / 6LowPAN Wireless Mesh Network sMAP Edge Router Temperature/PAR/TSR Vibration / Humidity AC plug meter Light switch Dent circuit meter Proxy Server EBHTTP Translation California ISO sMAP Gateway sMAP Resources Applications Google PowerMeter Weather sMAP Every Building Database

5 Live System with Big Data Importing old data: 150k points/secContinuous write load: pts/sec ~6 billion points from just a few buildings 1k points/building x 1 reading/30 seconds forever!

6 Building Information Load Tree Climate Plant Vibration Temperature Humidity Pressure CT: Mains Power Monitoring Panel Level Power Monitoring ACme: Plug Load Energy Monitor and Controller Operations and Environment

7 slicr: Tags Generate Multiple Views January 9, 2012Local Winter Retreat 2012 [ { tag : "Metadata/SourceName", restrict: "has Metadata/Extra/EndUse"}, { tag: "Metadata/Extra/EndUse"}, { tag: "Metadata/Extra/Category", defaultSubStream: "Properties/UnitofMeasure = 'mW'", seriesLabel:["Metadata/Location/Room", "Metadata/Extra/Load"]}, { tag: "Metadata/Extra/ProductType", defaultSubStream: "Properties/UnitofMeasure = 'mW'", seriesLabel:["Metadata/Location/Room", "Metadata/Extra/Load"]}, { tag: "Metadata/Instrument/PartNumber", defaultSubStream: "Properties/UnitofMeasure = 'mW'", seriesLabel:["Metadata/Instrument/PartNumber", "Metadata/Location/Room", "Metadata/Extra/Load”]}, "Properties/UnitofMeasure” ] 7

8 Model-Predictive HVAC Controls Occupant-responsive spaces Privacy-preserving database In 380 Soda Hall: Wozniak Lounge

9 9 Instrumentation Models Controls Building OS Plug Loads Lighting Facilities Building Instrumentation Models Routing/Control Grid OS Demand Response Load Following Supply Following Grid Facility-to- Building Gen-to- Building Instrumentation Models Control Compressor Scheduling Temperature Maintenance Supply-Following Loads Storage- to-Building Instrumentation Models Power-Aware Cluster Manager Load Balancer/ Scheduler Web Server Web App Logic DB/Storage Machine Room MR-to- Building Energy Networks Gen- to-Grid uGrid- to-Grid Building- to-Grid

10 72% of electrical consumption, 40% of total consumption, 50% with construction, 42% of GHG footprint Commercial building consumption 2x , 1.5x more by 2025 [NREL] Where the coal is used The prime target of opportunity for renewable supplies Save the world Renewable energy consumption Electricity source Software Controllable!

11 The sMAP library many different underlying sensors and stacks More then 100 instruments, > 500 ACme plug-load meters channels of high-resolution data It’s easy: simplest service is ~3 lines of Python

12 Real-Time Occupant Control Live on two floors 137 distinct users Over 50% energy savings (Krioukov et. al., proc. BuildSys ‘12)

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