Interpreting human activity from electrical consumption data through non-intrusive load monitoring
Author(s)
Gillman, Mark Daniel
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Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Steven B. Leeb and John S. Donnal.
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Non-intrusive load monitoring (NILM) has three distinct advantages over today's smart meters. First, it offers accountability. Few people know where their kWh's are going. Second, it is a maintenance tool. Signs of wear are detectable through their electrical signal. Third, it provides awareness of human activity within a network. Each device has an electrical fingerprint, and specific devices imply associated human actions. From voltage and current measurements at a single point on the network, non-intrusive load monitoring (NILM) disaggregates appliance-level information. This information is available remotely in bandwidth-constrained environments. Four real-world field tests at military micro grids and commercial buildings demonstrate the utility of the NILM in reducing electrical demand, enabling condition-based maintenance, and inferring human activity from electrical activity.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. 50 Cataloged from PDF version of thesis. Includes bibliographical references (pages 155-160).
Date issued
2014Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.