{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T14:15:04Z","timestamp":1761401704630,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,1,6]],"date-time":"2014-01-06T00:00:00Z","timestamp":1388966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.<\/jats:p>","DOI":"10.3390\/s140100848","type":"journal-article","created":{"date-parts":[[2014,1,6]],"date-time":"2014-01-06T11:17:08Z","timestamp":1389007028000},"page":"848-867","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques"],"prefix":"10.3390","volume":"14","author":[{"given":"Geraldo","family":"Filho","sequence":"first","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of S\u00e3o Paulo, S\u00e3o Carlos-SP 13566-590, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5591-3750","authenticated-orcid":false,"given":"J\u00f3","family":"Ueyama","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of S\u00e3o Paulo, S\u00e3o Carlos-SP 13566-590, Brazil"}]},{"given":"Leandro","family":"Villas","sequence":"additional","affiliation":[{"name":"Institute of Computing, University of Campinas, Campinas-SP 13083-852, Brazil"}]},{"given":"Alex","family":"Pinto","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Statistics, S\u00e3o Paulo State University, S\u00e3o Jos\u00e9 do Rio Preto-SP 15054-000, Brazil"}]},{"given":"Vin\u00edcius","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Computer Science, University of S\u00e3o Paulo, S\u00e3o Carlos-SP 13566-590, Brazil"}]},{"given":"Gustavo","family":"Pessin","sequence":"additional","affiliation":[{"name":"Vale Institute of Technology (ITV), Bel\u00b4em-PA 66055-090, Brazil"}]},{"given":"Richard","family":"Pazzi","sequence":"additional","affiliation":[{"name":"Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON 2000, Canada"}]},{"given":"Torsten","family":"Braun","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Applied Mathematics, University of Bern, Bern 3012, Switzerland"}]}],"member":"1968","published-online":{"date-parts":[[2014,1,6]]},"reference":[{"key":"ref_1","unstructured":"DATA World Development Indicators. 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