This document discusses how solar panels can provide electricity and reduce carbon emissions for homes. It explains that the cost per watt of solar panels has dropped 64% since 2010 due to increasing demand and incentives from cities and suppliers. The document presents a solar map that uses computer vision to analyze rooftop images and calculate a "solar score" to identify the most effective locations for installing solar panels based on factors like insulation, area, and installation costs. It provides examples of solar scores for homes in New York City and Los Angeles.

1. S O L A
R
M A P

2. For a typical home solar array, one
year of electricity (3.76MWh)
eliminates 2.5 tonnes CO2 and 7kg
of SO2

3. Since 2010,
$/watt
dropped 64%
Cost Demand
Incentives from
cities, suppliers
also driving demand

4. We find the most effective location to
install your solar panels.

5. Every roof
Every spot on a roof
For long-term cost and energy savings

7. Houston
San
Francisco
Louisville
Ithaca
Orlando
Boston
Boulder
Phoenix
Las
Vegas
Pittsburgh
Miami

8. System

12. Computer Vision

13. Computer Vision

14. Score
• S = Solar Score
• Radiance = kWh/m2
• A = Area of Roof
• $ = Unit Cost of Installation
• S = $/(R*A1/2)

16. Solar Score Map
New York City
Price : $18/unit
Insolation : 2.6
KWh/m2/day
Area : 234 m2
Los Angeles
Price : $16/unit
Insolation: 3.6 KWh/m2/day
Area: 290 m2

17. Potential Improvements
• Upgrading Score Function to Integral of
Cost Effectives over Time
• Better computer vision algorithms
• Pulling from Google Maps directly