Sensor-based big data applications and computationally networked urbanism in smart energy management systems

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Abstract

I draw on a substantial body of theoretical and empirical research on smart energy management systems. The data used for this study was obtained and replicated from previous research conducted by Energy B2B, Eurostat, PwC, Schneider Electric, and Statista. I performed analyses and made estimates regarding the rate of adoption of energy and resource efficiency, renewable energy, and other technologies and strategies. Data collected from 3,400 respondents are tested against the research model by using structural equation modeling.

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Eysenck, G. (2020). Sensor-based big data applications and computationally networked urbanism in smart energy management systems. Geopolitics, History, and International Relations, 12(1), 52–58. https://doi.org/10.22381/GHIR12120203

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