Title:
Detecting Actuation Of Electrical Devices Using Electrical Noise Over A Power Line

dc.contributor.patentcreator Patel, Shwetak N.
dc.contributor.patentcreator Robertson, Thomas M.
dc.contributor.patentcreator Abowd, Gregory D.
dc.contributor.patentcreator Reynolds, Matthew S.
dc.date.accessioned 2017-05-12T14:26:46Z
dc.date.available 2017-05-12T14:26:46Z
dc.date.filed 12/17/2012
dc.date.issued 2/2/2016
dc.description.abstract Activity sensing in the home has a variety of important applications, including healthcare, entertainment, home automation, energy monitoring and post-occupancy research studies. Many existing systems for detecting occupant activity require large numbers of sensors, invasive vision systems, or extensive installation procedures. Disclosed is an approach that uses a single plug-in sensor to detect a variety of electrical events throughout the home. This sensor detects the electrical noise on residential power lines created by the abrupt switching of electrical devices and the noise created by certain devices while in operation. Machine learning techniques are used to recognize electrically noisy events such as turning on or off a particular light switch, a television set, or an electric stove. The system has been tested to evaluate system performance over time and in different types of houses. Results indicate that various electrical events can be learned and classified with accuracies ranging from 85-90%.
dc.description.assignee Georgia Tech Research Corporation
dc.identifier.cpc H04B3/544
dc.identifier.cpc G01R21/006
dc.identifier.cpc G06F17/00
dc.identifier.patentapplicationnumber 13/717195
dc.identifier.patentnumber 9250275
dc.identifier.uri http://hdl.handle.net/1853/57050
dc.identifier.uspc 1-Jan
dc.title Detecting Actuation Of Electrical Devices Using Electrical Noise Over A Power Line
dc.type Text
dc.type.genre Patent
dspace.entity.type Publication
local.contributor.corporatename Georgia Institute of Technology
local.relation.ispartofseries Georgia Tech Patents
relation.isOrgUnitOfPublication cc30e153-7a64-4ae2-9b1d-5436686785e3
relation.isSeriesOfPublication 0f49c79d-4efb-4bd9-b060-5c7f9191b9da
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