peopleFaculty
Ram Rajagopal
Associate Professor of Civil and Environmental Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Electrical Engineering, Stanford University
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Associate Professor of Civil and Environmental Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Electrical Engineering, Stanford University
In this brief, Stanford scholars introduce a novel street-view image dataset and AI model as a more accurate proxy for detecting and assessing urban changes such as gentrification.
Residential solar panel usage is growing rapidly, as more households use photovoltaic (PV) technology to convert sunlight into electricity. But the deployment of residential solar PV has been highly unequal across the United States. Studying the spread of solar PV technology is vital to identifying and tackling barriers to adoption. In this brief, we present computer vision as an essential technique that can help policymakers understand residential solar usage. Our research uses computer vision to build a nationwide dataset to capture information about solar PV deployment in the United States across time and geography in an automated and scalable manner.
SCHMEAR: Scalable Construction of Holistic Models for Energy Analysis from Rooftops