Filho, Geraldo P R; Ueyama, Jó; Villas, Leandro A; Pinto, Alex R; Gonçalves, Vinícius P; Pessin, Gustavo; Pazzi, Richard W; Braun, Torsten (2014). NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques. Sensors, 14(1), pp. 848-867. Molecular Diversity Preservation International MDPI 10.3390/s140100848
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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.
|Item Type:||Journal Article (Original Article)|
|Division/Institute:||08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)
08 Faculty of Science > Institute of Computer Science (INF)
|UniBE Contributor:||Braun, Torsten|
|Subjects:||000 Computer science, knowledge & systems|
|Publisher:||Molecular Diversity Preservation International MDPI|
|Submitter:||Jonnahtan Eduardo Saltarin de Arco|
|Date Deposited:||15 Jan 2014 16:40|
|Last Modified:||12 Feb 2016 16:34|
|Uncontrolled Keywords:||smart grid; wireless sensor networks; electronic equipment; energy consumption; feedback|