Renewable energy is the future, but at present no one is tracking just who’s got solar panels on their roof, in their back yard, or a shared neighborhood installation. Fortunately, solar panels generally work best when exposed to the light. That makes them easy to spot, and count, from orbit — which is just what the DeepSolar project is doing.
There are a number of initiatives for collecting this information — some regulated, some voluntary, some automated. But none of them is comprehensive enough or accurate enough to base policy or business decisions on at a national or state level.
Stanford engineers (mechanical and civil, respectively) Arun Majumdar and Ram Rajagopal decided to remedy this with what seems like, in retrospect, rather an obvious solution.
Machine learning systems are great at looking at images and finding objects they’ve been “trained” to recognize, whether it’s cats, faces, or cars… so why not solar panels? [click for full article]