Modi’s team performed a statistical analysis to estimate New York City-specific building energy use. Their statistical model utilizes zipcode-level energy consumption data to estimate the average annual energy use for every tax lot—at practically building level—through all five boroughs of the city.
This energy use was further broken down into what the building uses for space heating, space cooling, water heating, and base electric applications such as lighting, and, with this information, the Columbia Engineering team created an interactive web map that shows what type of energy is being used, for which purpose, and in what quantity. “This map will enable NYC building owners to see whether their own building consumes more or less than what an average building with similar function and size would,” said Professor Modi. “This is the first time anyone has provided an estimate like this for New York City and the first time anyone has offered information to the public in the form of an interactive map.”
What’s next? We’d like to see someone combine this with peak use data and make certain devices smarter. For example, during peak times in the summer some appliances / devices would be “aware” what’s a good non-peak time to run. The IoT should know when it’s a good time to turn on, and off.
Eink, E-paper, Think Ink – Collin shares six segments pondering the unusual low-power display technology that somehow still seems a bit sci-fi – http://adafruit.com/thinkink
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