{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T19:47:25Z","timestamp":1768679245114,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Princess Nourah bint Abdulrahman University Researchers","award":["PNURSP2022R125"],"award-info":[{"award-number":["PNURSP2022R125"]}]},{"name":"Princess Nourah bint Abdulrahman University","award":["PNURSP2022R125"],"award-info":[{"award-number":["PNURSP2022R125"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>The evolution of applications in telecommunication, network, computing, and embedded systems has led to the emergence of the Internet of Things and Artificial Intelligence. The combination of these technologies enabled improving productivity by optimizing consumption and facilitating access to real-time information. In this work, there is a focus on Industry 4.0 and Smart City paradigms and a proposal of a new approach to monitor and track water consumption using an OCR, as well as the artificial intelligence algorithm and, in particular the YoLo 4 machine learning model. The goal of this work is to provide optimized results in real time. The recognition rate obtained with the proposed algorithms is around 98%.<\/jats:p>","DOI":"10.3390\/bdcc6030072","type":"journal-article","created":{"date-parts":[[2022,7,2]],"date-time":"2022-07-02T11:12:35Z","timestamp":1656760355000},"page":"72","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Lightweight AI Framework for Industry 4.0 Case Study: Water Meter Recognition"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0520-9415","authenticated-orcid":false,"given":"Jalel","family":"Ktari","sequence":"first","affiliation":[{"name":"CES Lab, ENIS, Sfax University, Sfax 3029, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8402-8059","authenticated-orcid":false,"given":"Tarek","family":"Frikha","sequence":"additional","affiliation":[{"name":"CES Lab, ENIS, Sfax University, Sfax 3029, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3690-9868","authenticated-orcid":false,"given":"Monia","family":"Hamdi","sequence":"additional","affiliation":[{"name":"Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2571-1848","authenticated-orcid":false,"given":"Hela","family":"Elmannai","sequence":"additional","affiliation":[{"name":"Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5320-1012","authenticated-orcid":false,"given":"Habib","family":"Hmam","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Universit\u00e9 de Moncton, Moncton, NB E1A3E9, Canada"},{"name":"Spectrum of Knowledge Production & Skills Development, Sfax 3027, Tunisia"},{"name":"International Institute of Technology and Management, Libreville BP1989, Gabon"},{"name":"Department of Electrical and Electronic Engineering Science, School of Electrical Engineering, University of Johannesburg, Johannesburg 2006, South Africa"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,1]]},"reference":[{"key":"ref_1","first-page":"861571","article-title":"Optimal Scheduling of Demand Side Load Management of Smart Grid Considering Energy Efficiiency","volume":"18","author":"Balouch","year":"2022","journal-title":"Energy Res."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Masood, B., Guobing, S., Nebhen, J., Rehman, A.U., Iqbal, M.N., Rasheed, I., Bajaj, M., Shafiq, M., and Hamam, H. 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