1. SDB Retreat Panel Session: Scalability Across the Building Stock Randy Katz, Moderator Arka Bhattacharya Kaifei Chen Stephen Dawson-Haggerty 1

2. What is Scalability? “… ability of a system to handle a growing amount of work in a capable manner or its ability to be enlarged to accommodate that growth.” “An algorithm scales if it is suitably efficient and practical when applied to large situations.” If modeling the SECOND building is less work than modeling the first 2 From wikipedia “Scalability” http://en.wikipedia.org/wiki/Scalability

3. Smart Buildings: How to Achieve Scale? Individual building deployments are Herculean efforts – Floorplans – Embedded system descriptions (lighting, HVAC, etc.) – Access to digital representations? Scale to millions of structures and 100s million of people? Automate the exploitation of existing information sources! 3

4. U.S. Building Stock Residential Buildings – 128 million residential housing units in U.S. (2007); 7.188 million new housing units built 2009 – 2009 Commercial Buildings – 4.9 million office buildings in the U.S. (2003); 170,000 commercial buildings constructed and 44,000 commercial buildings demolished per year (1995) 4

5. Existing Approaches for Awareness: Surveys California Commercial Energy Survey: – Random sample of 2,790 commercial facilities – Stratified by utility service area, climate region, building type, energy consumption level – Twelve common commercial building types: floor stocks, fuel shares, electric & natural gas consumption, energy-use indices, energy intensities, 16-day hourly end-use load profiles – See http://capabilities.itron.com/ceusweb/http://capabilities.itron.com/ceusweb/ 5

6. Existing Approach for Awareness: Surveys EIA Residential Survey – Interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics – Information combined with data from energy suppliers to estimate energy costs and usage for heating, cooling, appliances and other end uses – See http://www.eia.gov/consumption/residential/http://www.eia.gov/consumption/residential/ 6

7. Residential Energy Consumption Survey 113.6 million occupied housing units in USA in 2009 About 19,000 were selected for interviews Only about 15,300 were occupied primary residences and eligible About 12,100 responded to the survey, a response rate of about 79% 7

8. Alternative Idea: Google Earth Crowd sourcing: Harness volunteer efforts to create Google SketchUp 3D building models 8

9. SketchUp 3D Warehouse 9

10. Google Earth Sufficient information to validate building plans … – Estimate building square feet – Building orientation – Construction materials 10

11. Google Earth Berkeley Campus Number of floors Orientation of windows Roof facing Other analyses 11

12. Google Earth Berkeley Campus Not just “landmark” buildings, but apartment buildings, shops, residences, … 12

13. From Street Views to … Inside Views 13

14. Google Floor Plans 14

15. 15

16. From Street Views to … Inside Views 16

17. Not Just Google … 17

18. Mining Additional Information Sources: Zillow 18

19. Residential Information and Real Estate Analytics 19

20. Residential Information 20

21. Conclusions The Challenge: Achieving Scale – Exploit crowd-sourcing User generated 3D models and floor plans Exemplar buildings and automated model building – Exploit alternative information sources Satellite and street-view photos Digitized floor plans Real-estate databases Making the information actionable: energy and other analytics – Liveability, Walkability, Transport Scoring – Localization/Indoor Mapping – Other social analytics 21