title: NodePM: a remote monitoring alert system for energy consumption using probabilistic techniques.
abstract: 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.
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. geraldop@icmc.usp.br.
authors.forename: Geraldo P R
authors.initials: GP
authors.lastname: Filho
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. joueyama@icmc.usp.br.
authors.forename: Jó
authors.initials: J
authors.lastname: Ueyama
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. leandro@ic.unicamp.br.
authors.forename: Leandro A
authors.initials: LA
authors.lastname: Villas
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. arpinto@ibilce.unesp.br.
authors.forename: Alex R
authors.initials: AR
authors.lastname: Pinto
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. vpg@icmc.usp.br.
authors.forename: Vinícius P
authors.initials: VP
authors.lastname: Gonçalves
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. gustavo.pessin@vale.com.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Pessin
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. richard.pazzi@uoit.ca.
authors.forename: Richard W
authors.initials: RW
authors.lastname: Pazzi
authors.affiliation: Institute of Mathematics and Computer Science, University of São Paulo, São Carlos-SP 13566-590, Brazil. braun@iam.unibe.ch.
authors.forename: Torsten
authors.initials: T
authors.lastname: Braun
mesh_terms: D003195:Computer Communication Networks; D011211:Electric Power Supplies; D006801:Humans; D058998:Remote Sensing Technology; D059015:Wireless Technology