{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:54:24Z","timestamp":1776088464777,"version":"3.50.1"},"reference-count":0,"publisher":"Slovenian Association Informatika","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCAI"],"abstract":"<jats:p>The rapid expansion of the Internet of Things (IoT) in smart cities has necessitated efficient, real-time energy anomaly detection. However, complex hybrid deep learning models often exceed the computational capacity of Edge devices. This paper proposes a lightweight, 3-layer Artificial Neural Network (ANN) framework designed for Edge deployment. Using the LEAD (Large-scale Energy Anomaly Detection) dataset, we address class imbalance via the Synthetic Minority Over-sampling Technique (SMOTE). Our model achieves 98.4% accuracy, a macro F1-score of 0.93, and an AUC of 0.91. While these metrics are competitive with state-of-the-art hybrid models, our framework provides a significantly lower memory footprint and sub-millisecond inference latency, making it ideal for resource-constrained Edge environments.<\/jats:p>","DOI":"10.31449\/inf.v50i1.12670","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:05:46Z","timestamp":1776085546000},"source":"Crossref","is-referenced-by-count":0,"title":["A Lightweight Edge-Deployable ANN Model for Real-Time Energy Anomaly Detection in IoT-Driven Smart Grids"],"prefix":"10.31449","volume":"50","author":[{"given":"Sofiane","family":"Benabbes","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wael","family":"Aissaoui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rabah","family":"Boucetti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"16141","published-online":{"date-parts":[[2026,4,13]]},"container-title":["Informatica"],"original-title":[],"link":[{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/12670\/6607","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/12670\/6607","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:05:46Z","timestamp":1776085546000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/view\/12670"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,13]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,4,13]]}},"URL":"https:\/\/doi.org\/10.31449\/inf.v50i1.12670","relation":{},"ISSN":["1854-3871","0350-5596"],"issn-type":[{"value":"1854-3871","type":"electronic"},{"value":"0350-5596","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4,13]]}}}