Internet of Things based Smart Energy Audit using Evolutionary Fuzzy Association Rule Mining

Authors : Wirarama Wedashwara; I Gede Eka Wiantara Putra; Candra Ahmadi; I Wayan Agus Arimbawa
article cite 5 Year 2019
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Abstract

Energy audits are investigations, studies and examination of power vitality utilization, with the point of proficiency without lessening the exhibition of the system. The paper presented Internet of Things (IoT) based Smart Energy Audit by implementing electrical data collection using Wireless Sensor Network (WSN) and Decision Support System (DSS) using Evolutionary Fuzzy Association Rule Mining (EFARM). The developed system aims to collects data using IoT nodes and summarise data pattern using EFARM in interpretation of Fuzzy Rules and Tree Based Evolutionary Computation (EC). The evaluation performed in five rooms within a week and shown EFARM capable to: Interpreted patterns of electricity consumption in load samples by achieving a high average, confident and score; Compare consumption patterns between measurement areas and the type of measured load; Summarise the rules similarity between areas as general rules and dissimilarities that only exist in some areas as a specific rule, using singletree interpretation; Interpretation of comparison between power consumption patterns with measurable performance, namely temperature and light intensity.


Concepts :
Smart Grid Energy Management
article cite 5 Year 2019 source
SDGs
Affordable and clean energy
Citations by Year
YearCount
2019 5