{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:55:39Z","timestamp":1760144139735,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T00:00:00Z","timestamp":1710892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ARDITI\u2014Ag\u00eancia Regional para o Desenvolvimento da Investi-ga\u00e7\u00e3o, Tecnologia e Inova\u00e7\u00e3o","award":["M1420-09-5369-FSE-000002","UIDB\/50009\/2020","UIDB\/04674\/2020"],"award-info":[{"award-number":["M1420-09-5369-FSE-000002","UIDB\/50009\/2020","UIDB\/04674\/2020"]}]},{"name":"LARSyS","award":["M1420-09-5369-FSE-000002","UIDB\/50009\/2020","UIDB\/04674\/2020"],"award-info":[{"award-number":["M1420-09-5369-FSE-000002","UIDB\/50009\/2020","UIDB\/04674\/2020"]}]},{"name":"Center for Research in Mathematics and Applications (CIMA)","award":["M1420-09-5369-FSE-000002","UIDB\/50009\/2020","UIDB\/04674\/2020"],"award-info":[{"award-number":["M1420-09-5369-FSE-000002","UIDB\/50009\/2020","UIDB\/04674\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Electronics"],"abstract":"<jats:p>Traditional methods for water-level measurement usually employ permanent structures, such as a scale built into the water system, which is costly and laborious and can wash away with water. This research proposes a low-cost, automatic water-level estimator that can appraise the level without disturbing water flow or affecting the environment. The estimator was developed for urban areas of a volcanic island water channel, using machine learning to evaluate images captured by a low-cost remote monitoring system. For this purpose, images from over one year were collected. For better performance, captured images were processed by converting them to a proposed color space, named HLE, composed of hue, lightness, and edge. Multiple residual neural network architectures were examined. The best-performing model was ResNeXt, which achieved a mean absolute error of 1.14 cm using squeeze and excitation and data augmentation. An explainability analysis was carried out for transparency and a visual explanation. In addition, models were developed to predict water levels. Three models successfully forecasted the subsequent water levels for 10, 60, and 120 min, with mean absolute errors of 1.76 cm, 2.09 cm, and 2.34 cm, respectively. The models could follow slow and fast transitions, leading to a potential flooding risk-assessment mechanism.<\/jats:p>","DOI":"10.3390\/electronics13061145","type":"journal-article","created":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T13:09:36Z","timestamp":1710940176000},"page":"1145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Noncontact Automatic Water-Level Assessment and Prediction in an Urban Water Stream Channel of a Volcanic Island Using Deep Learning"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5107-3248","authenticated-orcid":false,"given":"F\u00e1bio","family":"Mendon\u00e7a","sequence":"first","affiliation":[{"name":"Faculty of Exact Sciences and Engineering, University of Madeira, 9020-105 Funchal, Portugal"},{"name":"Interactive Technologies Institute (ITI\/LARSyS) and ARDITI, 9020-105 Funchal, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7677-0971","authenticated-orcid":false,"given":"Sheikh Shanawaz","family":"Mostafa","sequence":"additional","affiliation":[{"name":"Interactive Technologies Institute (ITI\/LARSyS) and ARDITI, 9020-105 Funchal, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7334-3993","authenticated-orcid":false,"given":"Fernando","family":"Morgado-Dias","sequence":"additional","affiliation":[{"name":"Faculty of Exact Sciences and Engineering, University of Madeira, 9020-105 Funchal, Portugal"},{"name":"Interactive Technologies Institute (ITI\/LARSyS) and ARDITI, 9020-105 Funchal, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9060-7476","authenticated-orcid":false,"given":"Joaquim Am\u00e2ndio","family":"Azevedo","sequence":"additional","affiliation":[{"name":"Faculty of Exact Sciences and Engineering, University of Madeira, 9020-105 Funchal, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8512-965X","authenticated-orcid":false,"given":"Antonio G.","family":"Ravelo-Garc\u00eda","sequence":"additional","affiliation":[{"name":"Interactive Technologies Institute (ITI\/LARSyS) and ARDITI, 9020-105 Funchal, Portugal"},{"name":"Institute for Technological Development and Innovation in Communications, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas de Gran Canaria, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3860-3424","authenticated-orcid":false,"given":"Juan L.","family":"Navarro-Mesa","sequence":"additional","affiliation":[{"name":"Institute for Technological Development and Innovation in Communications, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas de Gran Canaria, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1080\/02626667.2014.967250","article-title":"Integrating Risks of Climate Change into Water Management","volume":"60","author":"Oki","year":"2015","journal-title":"Hydrol. 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