Testing the electromagnetic field signature for a hair dryer
We continue working with the Welch group at U of L on tracking appliance usage in homes and offices. The goal is for individuals to track their own energy consumption with mobile sensors. Here’s Dr. Welch’s Ph.D. student Anand Kulkarni running an appliance near a copper plane antenna to pick up its electromagnetic field (EMF) signature. Five appliances were classified using a decision tree algorithm. For more, see IEEE Sensors Journal:
1525082
PXS76R6R
items
1
0
default
asc
1
639
https://harnettlab.org/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3A%22zotpress-6c16353229da487bb419cddccdf34e78%22%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22PXS76R6R%22%2C%22library%22%3A%7B%22id%22%3A1525082%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Kulkarni%20et%20al.%22%2C%22parsedDate%22%3A%222015-06%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%3Cdiv%20class%3D%5C%22csl-bib-body%5C%22%20style%3D%5C%22line-height%3A%201.35%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%5C%22%3E%5Cn%20%20%3Cdiv%20class%3D%5C%22csl-entry%5C%22%3EKulkarni%2C%20A.%2C%20C.%20Harnett%2C%20and%20K.%20Welch.%202015.%20%26%23x201C%3BEMF%20Signature%20for%20Appliance%20Classification.%26%23x201D%3B%20%3Ci%3EIEEE%20Sensors%20Journal%3C%5C%2Fi%3E%2015%20%286%29%3A%203573%26%23x2013%3B81.%20%3Ca%20href%3D%27https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1109%5C%2FJSEN.2014.2379113%27%3Ehttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1109%5C%2FJSEN.2014.2379113%3C%5C%2Fa%3E.%3C%5C%2Fdiv%3E%5Cn%3C%5C%2Fdiv%3E%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22EMF%20Signature%20for%20Appliance%20Classification%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22A.%22%2C%22lastName%22%3A%22Kulkarni%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22C.%22%2C%22lastName%22%3A%22Harnett%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22K.%22%2C%22lastName%22%3A%22Welch%22%7D%5D%2C%22abstractNote%22%3A%22Various%20intrusive%20and%20nonintrusive%20appliance%20load%20monitoring%20and%20classification%20systems%20have%20been%20studied%3B%20however%2C%20most%20of%20them%20designed%20so%20far%20provide%20group-level%20energy%20usage%20feedback.%20We%20present%20the%20first%20phase%20of%20a%20system%20with%20the%20potential%20to%20attribute%20energy-related%20events%20to%20an%20individual%20occupant%20of%20a%20space%20and%20provide%20occupant-specific%20energy%20usage%20feedback%20in%20an%20un-instrumented%20space%20%28e.g.%2C%20home%20or%20office%29.%20This%20initial%20phase%20focuses%20on%20collecting%20the%20electromagnetic%20field%20%28EMF%29%20radiated%20by%20several%20common%20appliances%20to%20determine%20a%20unique%20signature%20for%20each%20appliance.%20It%20also%20implements%20a%20machine%20learning%20algorithm%20to%20classify%20appliances%20from%20an%20incoming%20EMF%20data%20file.%20The%20proposed%20approach%20has%20been%20prototyped%20with%20hardware%20realization.%20The%20results%20obtained%20on%20tested%20appliances%20indicate%20the%20EMF%20sensor%5Cu2019s%20ability%20and%20potential%20to%20develop%20a%20system%20for%20providing%20occupant-specific%20energy%20feedback.%22%2C%22date%22%3A%22June%202015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1109%5C%2FJSEN.2014.2379113%22%2C%22ISSN%22%3A%221530-437X%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Fieeexplore.ieee.org%5C%2Fxpls%5C%2Fabs_all.jsp%3Farnumber%3D6980072%22%2C%22collections%22%3A%5B%22GXXIZJ7F%22%5D%2C%22dateModified%22%3A%222016-05-10T13%3A55%3A16Z%22%7D%2C%22image%22%3A%5B%22https%3A%5C%2F%5C%2Fharnettlab.org%5C%2Fwp-content%5C%2Fuploads%5C%2F2015%5C%2F03%5C%2FHistogram.png%22%2C100%2C100%2Cfalse%5D%7D%5D%7D
Kulkarni, A., C. Harnett, and K. Welch. 2015. “EMF Signature for Appliance Classification.”
IEEE Sensors Journal 15 (6): 3573–81.
https://doi.org/10.1109/JSEN.2014.2379113 .