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.
Keywords: smart energy management system; networked urbanism; big data
How to cite: 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. doi:10.22381/GHIR12120203
Received 5 March 2020 • Received in revised form 26 May 2020
Accepted 28 May 2020 • Available online 24 June 2020