{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T11:53:56Z","timestamp":1781870036593,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T00:00:00Z","timestamp":1782086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"SWEDAC - Swedish Board for Accreditation and Conformity Assessment","award":["FO2023\/222"],"award-info":[{"award-number":["FO2023\/222"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,22]]},"DOI":"10.1145\/3744256.3812589","type":"proceedings-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T11:01:41Z","timestamp":1781866901000},"page":"271-281","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Federated Drift Monitoring for District Heating Meters Using Lightweight Statistical Signatures"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7450-4563","authenticated-orcid":false,"given":"Varsha","family":"Badgujar","sequence":"first","affiliation":[{"name":"University of Boras, Boras, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9685-7775","authenticated-orcid":false,"given":"Gideon","family":"Mbiydzenyuy","sequence":"additional","affiliation":[{"name":"University of Boras, Boras, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,22]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.5555\/151741"},{"key":"e_1_3_3_1_4_2","unstructured":"Daniel\u00a0J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques Yan Gao Lorenzo Sani Kwing\u00a0Hei Li Titouan Parcollet Pedro Porto\u00a0Buarque de Gusm\u00e3o and Nicholas\u00a0D. Lane. 2020. Flower: A Friendly Federated Learning Research Framework. arxiv:https:\/\/arXiv.org\/abs\/2007.14390\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/2007.14390"},{"key":"e_1_3_3_1_5_2","first-page":"374","volume-title":"Proceedings of Machine Learning and Systems 1 (MLSys 2019)","author":"Bonawitz Keith","year":"2019","unstructured":"Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chlo\u00e9 Kiddon, Jakub Konecn\u00fd, Stefano Mazzocchi, H.\u00a0Brendan McMahan, Timon Van\u00a0Overveldt, David Petrou, Daniel Ramage, and Jason Roselander. 2019. Towards Federated Learning at Scale: System Design. In Proceedings of Machine Learning and Systems 1 (MLSys 2019). MLSys, Palo Alto, CA, USA, 374\u2013388."},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","unstructured":"Varun Chandola Arindam Banerjee and Vipin Kumar. 2009. Anomaly Detection: A Survey. Comput. Surveys 41 3 Article 15 (2009) 58\u00a0pages. 10.1145\/1541880.1541882","DOI":"10.1145\/1541880.1541882"},{"key":"e_1_3_3_1_8_2","volume-title":"EN 1434-1: Thermal Energy Meters \u2013 Part 1: General Requirements","author":"(CEN) European Committee for Standardization","year":"2015","unstructured":"European Committee for Standardization (CEN). 2015. EN 1434-1: Thermal Energy Meters \u2013 Part 1: General Requirements. European Standard EN 1434-1. CEN, Brussels, Belgium."},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","unstructured":"Joao Gama Indre Zliobait Albert Bifet Mykola Pechenizkiy and Abdelhamid Bouchachia. 2014. A Survey on Concept Drift Adaptation. Comput. Surveys 46 4 Article 44 (2014) 37\u00a0pages. 10.1145\/2523813","DOI":"10.1145\/2523813"},{"key":"e_1_3_3_1_10_2","unstructured":"Arthur Gretton Karsten\u00a0M. Borgwardt Malte\u00a0J. Rasch Bernhard Scholkopf and Alexander\u00a0J. Smola. 2012. A Kernel Two-Sample Test. Journal of Machine Learning Research 13 (2012) 723\u2013773."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","unstructured":"David\u00a0V. Hinkley. 1970. Inference About the Change-Point in a Sequence of Random Variables. Biometrika 57 1 (1970) 1\u201317. 10.1093\/biomet\/57.1.1","DOI":"10.1093\/biomet\/57.1.1"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","unstructured":"J.\u00a0Edward Jackson and G.\u00a0S. Mudholkar. 1979. Control Procedures for Residuals Associated with Principal Component Analysis. Technometrics 21 3 (1979) 341\u2013349. 10.1080\/00401706.1979.10489779","DOI":"10.1080\/00401706.1979.10489779"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/b98835"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","unstructured":"Peter Kairouz H.\u00a0Brendan McMahan Brendan Avent et\u00a0al. 2021. Advances and Open Problems in Federated Learning. Foundations and Trends in Machine Learning 14 1\u20132 (2021) 1\u2013210. 10.1561\/2200000083","DOI":"10.1561\/2200000083"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","unstructured":"Srinivas Katipamula and Michael\u00a0R. Brambley. 2005. Methods for Fault Detection Diagnostics and Prognostics for Building Systems: A Review Part I. HVAC and R Research 11 1 (2005) 3\u201325. 10.1080\/10789669.2005.10391123","DOI":"10.1080\/10789669.2005.10391123"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Gary Lorden. 1971. Procedures for Reacting to a Change in Distribution. The Annals of Mathematical Statistics 42 6 (1971) 1897\u20131908.","DOI":"10.1214\/aoms\/1177693055"},{"key":"e_1_3_3_1_17_2","series-title":"Proceedings of Machine Learning Research","first-page":"1273","volume-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics","volume":"54","author":"McMahan H.\u00a0Brendan","year":"2017","unstructured":"H.\u00a0Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Ag\u00fcera\u00a0y Arcas. 2017. Communication-Efficient Learning of Deep Networks from Decentralized Data. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research, Vol.\u00a054). PMLR, Fort Lauderdale, FL, USA, 1273\u20131282."},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","unstructured":"P. Nomikos and J.\u00a0F. MacGregor. 1995. Multivariate Statistical Process Control Charts for Monitoring Batch Processes. Technometrics 37 1 (1995) 41\u201359. 10.1080\/00401706.1995.10485888","DOI":"10.1080\/00401706.1995.10485888"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","unstructured":"E.S. Page. 1954. Continuous Inspection Schemes. Biometrika 41 1\u20132 (1954) 100\u2013115. 10.1093\/biomet\/41.1-2.100","DOI":"10.1093\/biomet\/41.1-2.100"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","unstructured":"Gabriel Peyr\u00e9 and Marco Cuturi. 2019. Computational Optimal Transport. Foundations and Trends in Machine Learning 11 5\u20136 (2019) 355\u2013607. 10.1561\/2200000073","DOI":"10.1561\/2200000073"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","unstructured":"S.\u00a0Joe Qin. 2003. Statistical Process Monitoring: A Review and Extensions. Journal of Chemometrics 17 8\u20139 (2003) 480\u2013502. 10.1002\/cem.800","DOI":"10.1002\/cem.800"},{"key":"e_1_3_3_1_22_2","first-page":"13458","volume-title":"Advances in Neural Information Processing Systems","author":"Rabanser Stephan","year":"2019","unstructured":"Stephan Rabanser, Stephan Gunnemann, and Zachary\u00a0C. Lipton. 2019. Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift. In Advances in Neural Information Processing Systems , Vol.\u00a032. Curran Associates, Inc., Red Hook, NY, USA, 13458\u201313469."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-71050-9"}],"event":{"name":"BuildSys '26: The 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","location":"Banff Canada","acronym":"BuildSys '26","sponsor":["SIGEnergy ACM Special Interest Group on Energy Systems and Informatics"]},"container-title":["Proceedings of the 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation"],"original-title":[],"deposited":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T11:28:47Z","timestamp":1781868527000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3744256.3812589"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,22]]},"references-count":22,"alternative-id":["10.1145\/3744256.3812589","10.1145\/3744256"],"URL":"https:\/\/doi.org\/10.1145\/3744256.3812589","relation":{},"subject":[],"published":{"date-parts":[[2026,6,22]]},"assertion":[{"value":"2026-06-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}