Loading…
Designing a Novel Dataset for Non-intrusive Load Monitoring
Non-intrusive Load Monitoring (NILM) is a technology that allows the identification of individual electrical loads from a single aggregated measurement of voltage/current, hence, useful for diagnostic of the consumption of electrical energy. This is performed by means of load detection and disaggreg...
Saved in:
Main Authors: | , , , , , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c222t-4cae436c742892f27efd13273d6521ad156ff44ff7ad3c938f397ab1bb021ad43 |
---|---|
cites | |
container_end_page | 249 |
container_issue | |
container_start_page | 243 |
container_title | |
container_volume | |
creator | Renaux, Douglas Linhares, Robson Pottker, Fabiana Lazzaretti, Andre Lima, Carlos Coelho Neto, Adil Campaner, Mateus |
description | Non-intrusive Load Monitoring (NILM) is a technology that allows the identification of individual electrical loads from a single aggregated measurement of voltage/current, hence, useful for diagnostic of the consumption of electrical energy. This is performed by means of load detection and disaggregation techniques, as there are several different power signatures from the active loads. In order to develop more precise and efficient strategies and algorithms for load detection and disaggregation, several efforts have been made to build datasets that represent different scenarios of combined power loads and the events that cause changes in their states, such as power on and power off. The research presented here shows the conception of a new dataset for NILM research, from the analysis of the limitations of existing datasets, as well as the development and evaluation of a data collecting jig that is being used to collect this dataset. As a result, the infrastructure has been set up to build the LIT dataset, which is expected to provide the NILM field of study with more precise data for power signature analysis. |
doi_str_mv | 10.1109/SBESC.2018.00045 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_8691975</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8691975</ieee_id><sourcerecordid>8691975</sourcerecordid><originalsourceid>FETCH-LOGICAL-c222t-4cae436c742892f27efd13273d6521ad156ff44ff7ad3c938f397ab1bb021ad43</originalsourceid><addsrcrecordid>eNotjFFLwzAUhaMgOOfeBV_yB1pzb26aBJ-0mzro9GH6PNI2GZHZSlMH_nsr-nTgfOc7jF2ByAGEvdner7ZljgJMLoQgdcIuQKMBgSTUKZuhRMq0sXTOFim9TxsQRilLM3a79Cnuu9jtuePP_dEf-NKNLvmRh36Ymi6L3Th8pXj0vOpdyzd9F8d-mIxLdhbcIfnFf87Z28PqtXzKqpfHdXlXZQ0ijhk1zpMsGk1oLAbUPrQgUcu2UAiuBVWEQBSCdq1srDRBWu1qqGvxi0nO2fXfb_Te7z6H-OGG750pLFit5A-pUEcx</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Designing a Novel Dataset for Non-intrusive Load Monitoring</title><source>IEEE Xplore All Conference Series</source><creator>Renaux, Douglas ; Linhares, Robson ; Pottker, Fabiana ; Lazzaretti, Andre ; Lima, Carlos ; Coelho Neto, Adil ; Campaner, Mateus</creator><creatorcontrib>Renaux, Douglas ; Linhares, Robson ; Pottker, Fabiana ; Lazzaretti, Andre ; Lima, Carlos ; Coelho Neto, Adil ; Campaner, Mateus</creatorcontrib><description>Non-intrusive Load Monitoring (NILM) is a technology that allows the identification of individual electrical loads from a single aggregated measurement of voltage/current, hence, useful for diagnostic of the consumption of electrical energy. This is performed by means of load detection and disaggregation techniques, as there are several different power signatures from the active loads. In order to develop more precise and efficient strategies and algorithms for load detection and disaggregation, several efforts have been made to build datasets that represent different scenarios of combined power loads and the events that cause changes in their states, such as power on and power off. The research presented here shows the conception of a new dataset for NILM research, from the analysis of the limitations of existing datasets, as well as the development and evaluation of a data collecting jig that is being used to collect this dataset. As a result, the infrastructure has been set up to build the LIT dataset, which is expected to provide the NILM field of study with more precise data for power signature analysis.</description><identifier>EISSN: 2324-7894</identifier><identifier>EISBN: 1728102405</identifier><identifier>EISBN: 9781728102405</identifier><identifier>DOI: 10.1109/SBESC.2018.00045</identifier><identifier>CODEN: IEEPAD</identifier><language>eng</language><publisher>IEEE</publisher><subject>Current measurement ; Dataset ; Dataset collecting jig ; Fixtures ; Home appliances ; Monitoring ; Non-Intrusive Load Monitoring ; Sensors ; Switches ; Thyristors</subject><ispartof>2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC), 2018, p.243-249</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c222t-4cae436c742892f27efd13273d6521ad156ff44ff7ad3c938f397ab1bb021ad43</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8691975$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,23930,23931,25140,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8691975$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Renaux, Douglas</creatorcontrib><creatorcontrib>Linhares, Robson</creatorcontrib><creatorcontrib>Pottker, Fabiana</creatorcontrib><creatorcontrib>Lazzaretti, Andre</creatorcontrib><creatorcontrib>Lima, Carlos</creatorcontrib><creatorcontrib>Coelho Neto, Adil</creatorcontrib><creatorcontrib>Campaner, Mateus</creatorcontrib><title>Designing a Novel Dataset for Non-intrusive Load Monitoring</title><title>2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC)</title><addtitle>SBESC</addtitle><description>Non-intrusive Load Monitoring (NILM) is a technology that allows the identification of individual electrical loads from a single aggregated measurement of voltage/current, hence, useful for diagnostic of the consumption of electrical energy. This is performed by means of load detection and disaggregation techniques, as there are several different power signatures from the active loads. In order to develop more precise and efficient strategies and algorithms for load detection and disaggregation, several efforts have been made to build datasets that represent different scenarios of combined power loads and the events that cause changes in their states, such as power on and power off. The research presented here shows the conception of a new dataset for NILM research, from the analysis of the limitations of existing datasets, as well as the development and evaluation of a data collecting jig that is being used to collect this dataset. As a result, the infrastructure has been set up to build the LIT dataset, which is expected to provide the NILM field of study with more precise data for power signature analysis.</description><subject>Current measurement</subject><subject>Dataset</subject><subject>Dataset collecting jig</subject><subject>Fixtures</subject><subject>Home appliances</subject><subject>Monitoring</subject><subject>Non-Intrusive Load Monitoring</subject><subject>Sensors</subject><subject>Switches</subject><subject>Thyristors</subject><issn>2324-7894</issn><isbn>1728102405</isbn><isbn>9781728102405</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2018</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjFFLwzAUhaMgOOfeBV_yB1pzb26aBJ-0mzro9GH6PNI2GZHZSlMH_nsr-nTgfOc7jF2ByAGEvdner7ZljgJMLoQgdcIuQKMBgSTUKZuhRMq0sXTOFim9TxsQRilLM3a79Cnuu9jtuePP_dEf-NKNLvmRh36Ymi6L3Th8pXj0vOpdyzd9F8d-mIxLdhbcIfnFf87Z28PqtXzKqpfHdXlXZQ0ijhk1zpMsGk1oLAbUPrQgUcu2UAiuBVWEQBSCdq1srDRBWu1qqGvxi0nO2fXfb_Te7z6H-OGG750pLFit5A-pUEcx</recordid><startdate>201811</startdate><enddate>201811</enddate><creator>Renaux, Douglas</creator><creator>Linhares, Robson</creator><creator>Pottker, Fabiana</creator><creator>Lazzaretti, Andre</creator><creator>Lima, Carlos</creator><creator>Coelho Neto, Adil</creator><creator>Campaner, Mateus</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201811</creationdate><title>Designing a Novel Dataset for Non-intrusive Load Monitoring</title><author>Renaux, Douglas ; Linhares, Robson ; Pottker, Fabiana ; Lazzaretti, Andre ; Lima, Carlos ; Coelho Neto, Adil ; Campaner, Mateus</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c222t-4cae436c742892f27efd13273d6521ad156ff44ff7ad3c938f397ab1bb021ad43</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Current measurement</topic><topic>Dataset</topic><topic>Dataset collecting jig</topic><topic>Fixtures</topic><topic>Home appliances</topic><topic>Monitoring</topic><topic>Non-Intrusive Load Monitoring</topic><topic>Sensors</topic><topic>Switches</topic><topic>Thyristors</topic><toplevel>online_resources</toplevel><creatorcontrib>Renaux, Douglas</creatorcontrib><creatorcontrib>Linhares, Robson</creatorcontrib><creatorcontrib>Pottker, Fabiana</creatorcontrib><creatorcontrib>Lazzaretti, Andre</creatorcontrib><creatorcontrib>Lima, Carlos</creatorcontrib><creatorcontrib>Coelho Neto, Adil</creatorcontrib><creatorcontrib>Campaner, Mateus</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Renaux, Douglas</au><au>Linhares, Robson</au><au>Pottker, Fabiana</au><au>Lazzaretti, Andre</au><au>Lima, Carlos</au><au>Coelho Neto, Adil</au><au>Campaner, Mateus</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Designing a Novel Dataset for Non-intrusive Load Monitoring</atitle><btitle>2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC)</btitle><stitle>SBESC</stitle><date>2018-11</date><risdate>2018</risdate><spage>243</spage><epage>249</epage><pages>243-249</pages><eissn>2324-7894</eissn><eisbn>1728102405</eisbn><eisbn>9781728102405</eisbn><coden>IEEPAD</coden><abstract>Non-intrusive Load Monitoring (NILM) is a technology that allows the identification of individual electrical loads from a single aggregated measurement of voltage/current, hence, useful for diagnostic of the consumption of electrical energy. This is performed by means of load detection and disaggregation techniques, as there are several different power signatures from the active loads. In order to develop more precise and efficient strategies and algorithms for load detection and disaggregation, several efforts have been made to build datasets that represent different scenarios of combined power loads and the events that cause changes in their states, such as power on and power off. The research presented here shows the conception of a new dataset for NILM research, from the analysis of the limitations of existing datasets, as well as the development and evaluation of a data collecting jig that is being used to collect this dataset. As a result, the infrastructure has been set up to build the LIT dataset, which is expected to provide the NILM field of study with more precise data for power signature analysis.</abstract><pub>IEEE</pub><doi>10.1109/SBESC.2018.00045</doi><tpages>7</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | EISSN: 2324-7894 |
ispartof | 2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC), 2018, p.243-249 |
issn | 2324-7894 |
language | eng |
recordid | cdi_ieee_primary_8691975 |
source | IEEE Xplore All Conference Series |
subjects | Current measurement Dataset Dataset collecting jig Fixtures Home appliances Monitoring Non-Intrusive Load Monitoring Sensors Switches Thyristors |
title | Designing a Novel Dataset for Non-intrusive Load Monitoring |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T21%3A30%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Designing%20a%20Novel%20Dataset%20for%20Non-intrusive%20Load%20Monitoring&rft.btitle=2018%20VIII%20Brazilian%20Symposium%20on%20Computing%20Systems%20Engineering%20(SBESC)&rft.au=Renaux,%20Douglas&rft.date=2018-11&rft.spage=243&rft.epage=249&rft.pages=243-249&rft.eissn=2324-7894&rft.coden=IEEPAD&rft_id=info:doi/10.1109/SBESC.2018.00045&rft.eisbn=1728102405&rft.eisbn_list=9781728102405&rft_dat=%3Cieee_CHZPO%3E8691975%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c222t-4cae436c742892f27efd13273d6521ad156ff44ff7ad3c938f397ab1bb021ad43%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=8691975&rfr_iscdi=true |