{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T22:47:48Z","timestamp":1781650068703,"version":"3.54.5"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004055","name":"Saudi Data and AI Authority (SDAIA) and the King Fahd University of Petroleum and Minerals (KFUPM) under SDAIA\u2013KFUPM Joint Research Center for Artificial Intelligence (JRC-AI) Fellowship Program","doi-asserted-by":"publisher","award":["JRC-AI-RFP-04"],"award-info":[{"award-number":["JRC-AI-RFP-04"]}],"id":[{"id":"10.13039\/501100004055","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3297552","type":"journal-article","created":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T17:56:11Z","timestamp":1689875771000},"page":"75599-75616","source":"Crossref","is-referenced-by-count":15,"title":["Contextual Sequence-to-Point Deep Learning for Household Energy Disaggregation"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1811-4933","authenticated-orcid":false,"given":"Mohammed","family":"Ayub","sequence":"first","affiliation":[{"name":"Department of Information and Computer Science, College of Computing and Mathematics, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6279-9776","authenticated-orcid":false,"given":"El-Sayed M.","family":"El-Alfy","sequence":"additional","affiliation":[{"name":"SDAIA-KFUPM Joint Research Center for Artificial Intelligence (SDAIA JRC-AI), Dhahran, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2019.04.110"},{"key":"ref57","first-page":"1","article-title":"The U.K.-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five U.K. homes","volume":"2","author":"kelly","year":"2015","journal-title":"Data Science Journal"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2821650.2821672"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2021.103321"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/su11113222"},{"key":"ref59","first-page":"673","article-title":"Bayesian nonparametric hidden semi-Markov models","volume":"14","author":"johnson","year":"2013","journal-title":"J Mach Learn Res"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2018.02.002"},{"key":"ref58","first-page":"59","article-title":"REDD: A public data set for energy disaggregation research","volume":"25","author":"kolter","year":"2011","journal-title":"Proc Workshop Data Mining Appl Sustainability (SIGKDD)"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.3390\/s22145250"},{"key":"ref52","article-title":"Multi-target XGBoostLSS regression","author":"m\u00e4rz","year":"2022","journal-title":"arXiv 2210 06831"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11873"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-019-0212-5"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1049\/joe.2018.8352"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.1049"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/en12071217"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2886849"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2023.121078"},{"key":"ref18","article-title":"A federated learning framework for non-intrusive load monitoring","author":"wang","year":"2021","journal-title":"arXiv 2104 01618"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3390\/s23042051"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113669"},{"key":"ref46","first-page":"54","article-title":"Household energy disaggregation based on pattern consumption similarities","author":"chavat","year":"2019","journal-title":"Proc Ibero-Amer Congr Inf Manage Big Data"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1186\/s13634-020-0664-y"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.segan.2019.100244"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682543"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE.2016.7726786"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2888581"},{"key":"ref44","article-title":"Deep learning based energy disaggregation and on\/off detection of household appliances","author":"jiang","year":"2019","journal-title":"arXiv 1908 00941"},{"key":"ref43","first-page":"1","article-title":"Semi-supervised energy disaggregation for real-world adoption","author":"kohl","year":"2021","journal-title":"Proc 29th Eur Conf Inf Syst (ECIS)"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2021.107347"},{"key":"ref8","article-title":"Non-intrusive load monitoring (NILM) using deep neural networks: A review","author":"azad","year":"2023","journal-title":"arXiv 2306 05017"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2022.108673"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/4216281"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2019.2918922"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2017.03.061"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/s22155872"},{"key":"ref5","author":"hart","year":"1989","journal-title":"Non-intrusive Appliance Monitor Apparatus"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3390\/en12142804"},{"key":"ref35","article-title":"Transfer learning for non-intrusive load monitoring and appliance identification in a smart home","author":"shahab","year":"2023","journal-title":"arXiv 2301 03018"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053947"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2023.3237862"},{"key":"ref36","first-page":"75","article-title":"Nonintrusive load monitoring based on sequence-to-sequence model with attention mechanism","volume":"39","author":"wang","year":"2019","journal-title":"Proc Chin Soc Electr Eng"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2865702"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2019.2953225"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3427771.3427845"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2923742"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.636"},{"key":"ref1","author":"ehrhardt-martinez","year":"2010","journal-title":"Advanced Metering Initiatives and Residential Feedback Programs A Meta-Review for Household Electricity-Saving Opportunities"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/en14040847"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.3390\/s22082926"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/en12071371"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.14569\/IJACSA.2020.0111085"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/en12091696"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2017.11.054"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2017.09.087"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/en12152882"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2019.2938068"},{"key":"ref64","author":"bonfigli","year":"2019","journal-title":"Machine Learning Approaches to Non-Intrusive Load Monitoring"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04747-3_26"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/SEGE.2018.8499519"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1186\/s42162-018-0038-y"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011150"},{"key":"ref65","first-page":"1472","article-title":"Approximate inference in additive factorial HMMs with application to energy disaggregation","author":"kolter","year":"2012","journal-title":"Proc 15th Int Conf Artif Intell Statist"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2019.01.034"},{"key":"ref27","first-page":"2961","article-title":"A convolutional autoencoder-based approach with batch normalization for energy disaggregation","volume":"76","author":"chen","year":"2020","journal-title":"J Supercomput"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/app10041454"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.3390\/inventions3030045"},{"key":"ref62","first-page":"30","article-title":"Nonintrusive energy disaggregation by detecting similarities in consumption patterns","author":"graneri","year":"2021","journal-title":"Revista Facultad de Ingeniera-Universidad de Antioquia"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06106-3"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10188822.pdf?arnumber=10188822","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T18:06:52Z","timestamp":1692036412000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10188822\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":68,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3297552","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}