Author Archives: Carl Elkin

Using machine learning to help people make smart decisions about solar energy

 A few years ago, when my family was first deciding whether or not to go solar, I remember driving around the neighborhood, looking at all the solar arrays on nearby rooftops. It made me realize: Wow, solar isn’t some futuristic concept, it’s already part of the fabric of my town! Seeing that others around me were already benefiting from solar helped me decide to do the same.

We want to make it easy for people to make informed decisions about whether to invest in solar. Project Sunroof already shows you solar potential and cost saving for more than 60 million individual homes. Today we’re adding a new feature, Project Sunroof Data Explorer, which shows a map of existing solar installations in neighborhoods throughout the United States. Now instead of driving street to street, it’s a little easier to see if houses around you and communities nearby have already gone solar.  
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Click on “existing arrays” in the upper right corner to see number of existing installations in your region

This feature combines machine learning with imagery from Google Maps and Google Earth to provide an estimate of how many houses in an area have solar. We started by taking in high-resolution imagery of rooftops and manually identifying solar installations. We then used that data as the initial training set for our algorithm. After many iterations, our machine learning algorithms can now automatically find and identify installations in the imagery (both photovoltaic panels, which produce electricity, and solar hot water heaters). Even for machines, practice makes perfect!

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So far we’ve identified around 700,000 installations in the U.S. and over time, as we continue to train the algorithms and apply improvements, we will be able to find and show more installations. We hope that this new feature will provide policy makers, communities and individuals with more information to help make smarter decisions in their transition to cleaner power sources.

Source: Google LatLong


Using machine learning to help people make smart decisions about solar energy

 A few years ago, when my family was first deciding whether or not to go solar, I remember driving around the neighborhood, looking at all the solar arrays on nearby rooftops. It made me realize: Wow, solar isn’t some futuristic concept, it’s already part of the fabric of my town! Seeing that others around me were already benefiting from solar helped me decide to do the same.

We want to make it easy for people to make informed decisions about whether to invest in solar. Project Sunroof already shows you solar potential and cost saving for more than 60 million individual homes. Today we’re adding a new feature, Project Sunroof Data Explorer, which shows a map of existing solar installations in neighborhoods throughout the United States. Now instead of driving street to street, it’s a little easier to see if houses around you and communities nearby have already gone solar.  
one
Click on “existing arrays” in the upper right corner to see number of existing installations in your region

This feature combines machine learning with imagery from Google Maps and Google Earth to provide an estimate of how many houses in an area have solar. We started by taking in high-resolution imagery of rooftops and manually identifying solar installations. We then used that data as the initial training set for our algorithm. After many iterations, our machine learning algorithms can now automatically find and identify installations in the imagery (both photovoltaic panels, which produce electricity, and solar hot water heaters). Even for machines, practice makes perfect!

2

So far we’ve identified around 700,000 installations in the U.S. and over time, as we continue to train the algorithms and apply improvements, we will be able to find and show more installations. We hope that this new feature will provide policy makers, communities and individuals with more information to help make smarter decisions in their transition to cleaner power sources.

Using machine learning to help people make smart decisions about solar energy

 A few years ago, when my family was first deciding whether or not to go solar, I remember driving around the neighborhood, looking at all the solar arrays on nearby rooftops. It made me realize: Wow, solar isn’t some futuristic concept, it’s already part of the fabric of my town! Seeing that others around me were already benefiting from solar helped me decide to do the same.

We want to make it easy for people to make informed decisions about whether to invest in solar. Project Sunroof already shows you solar potential and cost saving for more than 60 million individual homes. Today we’re adding a new feature, Project Sunroof Data Explorer, which shows a map of existing solar installations in neighborhoods throughout the United States. Now instead of driving street to street, it’s a little easier to see if houses around you and communities nearby have already gone solar.  
one
Click on “existing arrays” in the upper right corner to see number of existing installations in your region

This feature combines machine learning with imagery from Google Maps and Google Earth to provide an estimate of how many houses in an area have solar. We started by taking in high-resolution imagery of rooftops and manually identifying solar installations. We then used that data as the initial training set for our algorithm. After many iterations, our machine learning algorithms can now automatically find and identify installations in the imagery (both photovoltaic panels, which produce electricity, and solar hot water heaters). Even for machines, practice makes perfect!

2

So far we’ve identified around 700,000 installations in the U.S. and over time, as we continue to train the algorithms and apply improvements, we will be able to find and show more installations. We hope that this new feature will provide policy makers, communities and individuals with more information to help make smarter decisions in their transition to cleaner power sources.

Going #SolarforSolstice with Project Sunroof and the Sierra Club

Join us in celebrating the start of summer in the Northern Hemisphere—the longest and brightest day of the year, when the Northern Hemisphere is tilted towards the sun more than any other day. Among the many gifts that summer brings—longer days, warm walks, and late evening dinners—solar energy is a largely underutilized benefit.

The sun delivers more energy to Earth in one hour than civilization uses in a whole year. On this long Summer Solstice day, solar panels on your roof could generate enough energy to run your refrigerator for almost two weeks—that’s 50 percent more energy than the average day. Yet globally only about 1 percent of our energy comes from solar. So today, Project Sunroof teamed up with the Sierra Club to share some tips on how you can better use the sun to generate energy and protect our Earth. 

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Solar energy is one of the cleanest energy sources available, and the U.S. has abundant solar resources. Project Sunroof is our attempt to make going solar a little easier. Homeowners can search their property and get a solar recommendation based on roof size, the amount of sun that hits it throughout the year, weather, applicable government incentives, and electricity rates and bill.

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Whether or not solar is an option for you, the Sierra Club has some additional tips on how to use the power of the sun and other forms of clean energy to slow the impacts of climate change. Check out Ready for 100 to learn more about how you can help us achieve 100% clean, renewable energy across the United States.

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