He and his colleagues built their system around carbon dioxide and passive infrared (PIR) sensors. The results are described in a study published 6 April in IEEE Internet of Things Journal.Īndres Rico is a graduate research assistant at the MIT Media Lab’s City Science Group who was involved in the study. It was recently tested in two different environments over the course of a month, and could predict human activity with 87 to 99 percent accuracy after just one week of training. However, there have been privacy concerns when it comes to these systems monitoring peoples’ activity, and smart-home systems can require heavy amounts of data crunching to learn how to respond to a given environment.Ī new smart system, dubbed Chameleon, is designed to address both of these issues. ![]() ![]() By sensing human activity and adjusting the environmental settings accordingly, smart-home systems could help create more energy-efficient and sustainable buildings.
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