Artículos de revistas
NodePM: a remote monitoring alert system for energy consumption using probabilistic techniques
Fecha
2014-01Registro en:
Sensors, Basel, v.14, n.1, p.848-867, 2014
10.3390/s140100848
Autor
Filho, Geraldo Pereira Rocha
Ueyama, Jo
Villas, Leandro Aparecido
Pinto, Alex Sandro Roschildt
Gonçalves, Vinicius Pereira
Pessin, Gustavo
Pazzi, Richard Werner Nelem
Torsten, Braun
Institución
Resumen
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.