{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:55:54Z","timestamp":1776887754875,"version":"3.51.2"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T00:00:00Z","timestamp":1686009600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Bavarian State Ministry of Family Affairs, Labor, and Social Affairs"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>Human activity event recognition (HAER) within a residence is a topic of significant interest in the field of ambient assisted living (AAL). Commonly, various sensors are installed within a residence to enable the monitoring of people. This work presents a new approach for HAER within a residence by (re-)using measurements from commercial smart water meters. Our approach is based on the assumption that changes in water flow within a residence, specifically the transition from no flow to flow above a certain threshold, indicate human activity. Using a separate, labeled evaluation data set from three households that was collected under controlled\/laboratory-like conditions, we assess the performance of our HAER method. Our results showed that the approach has a high precision (0.86) and recall (1.00). Within this work, we further recorded a new open data set of water consumption data in 17 German households with a median sample rate of 0.083\u00af Hz to demonstrate that water flow data are sufficient to detect activity events within a regular daily routine. Overall, this article demonstrates that smart water meter data can be effectively used for HAER within a residence.<\/jats:p>","DOI":"10.3390\/jsan12030046","type":"journal-article","created":{"date-parts":[[2023,6,7]],"date-time":"2023-06-07T02:02:15Z","timestamp":1686103335000},"page":"46","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Exploiting Smart Meter Water Consumption Measurements for Human Activity Event Recognition"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4370-9234","authenticated-orcid":false,"given":"Sebastian","family":"Wilhelm","sequence":"first","affiliation":[{"name":"Deggendorf Institute of Technology; Technology Campus Grafenau, 94481 Grafenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7628-7296","authenticated-orcid":false,"given":"Jakob","family":"Kasbauer","sequence":"additional","affiliation":[{"name":"Deggendorf Institute of Technology; Technology Campus Grafenau, 94481 Grafenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3542-2142","authenticated-orcid":false,"given":"Dietmar","family":"Jakob","sequence":"additional","affiliation":[{"name":"Deggendorf Institute of Technology; Technology Campus Grafenau, 94481 Grafenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6029-4424","authenticated-orcid":false,"given":"Benedikt","family":"Elser","sequence":"additional","affiliation":[{"name":"Deggendorf Institute of Technology; Technology Campus Grafenau, 94481 Grafenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9905-7442","authenticated-orcid":false,"given":"Diane","family":"Ahrens","sequence":"additional","affiliation":[{"name":"Deggendorf Institute of Technology; Technology Campus Grafenau, 94481 Grafenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ann, O.C., and Theng, L.B. 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