Abstract
Purpose
This paper aims to focus on data analytic tools and integrated data analyzing approaches used on smart energy meters (SEMs). Furthermore, while observing the diverse techniques and frameworks of data analysis of SEM, the authors propose a novel framework for SEM by using gamification approach for enhancing the involvement of consumers to conserve energy and improve efficiency.
Design/methodology/approach
A few research strategies have been accounted for analyzing the raw data, yet at the same time, a considerable measure of work should be done in making these commercially reasonable. Data analytic tools and integrated data analyzing approaches are used on SEMs. Furthermore, while observing the diverse techniques and frameworks of data analysis of SEM, the authors propose a novel framework for SEM by using gamification approach for enhancing the involvement of consumers to conserve energy and improve efficiency. Advantages of SEM’s are additionally discussed for inspiring consumers, utilities and their respective partners.
Findings
Consumers, utilities and researchers can also take benefit of the recommended framework by planning their routine activities and enjoying rewards offered by gamification approach. Through gamification, consumers’ commitment enhances, and it changes their less manageable conduct on an intentional premise. The practical implementation of such approaches showed the improved energy efficiency as a consequence.
Subject
Strategy and Management,General Energy
Reference135 articles.
1. Electricity peak demand consumption management;Analytics case study by Deloitte,2014
2. Principal component analysis;Wiley Interdisciplinary Reviews: Computational Statistics,2010
3. A contribution to better understand the demand for electricity in the residential sector;Procedure European Council Energy Efficient Economy (ECEEE’11) Summer Study,2011
4. Using pattern recognition to identify habitual behavior in residential electricity consumption;Energy and Buildings,2012
5. A novel SVM-KNN-PSO ensemble method for intrusion detection system;Applied Soft Computing,2016
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