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Title: Evaluating the Resilience of the Bottom-up Method used to Detect and Benchmark the Smartness of University Campuses
Authors: Giovannella, Carlo
Andone, Diana
Dascalu, Mihai
Popescu, Elvira
Rehm, Matthias
Mealha, Oscar
Keywords: smart city learning
learning ecosystems
smart city analytics
flow state
Maslow pyramid
Principal Component Analysis
Issue Date: Jan-2017
Publisher: IEEE
Citation: Giovannella, C., Andone, D., Dascalu, M., Popescu, E., Rehm, M., & Mealha, O. (2016). Evaluating the Resilience of the Bottom-up Extraction Method used to Benchmark the Smartness of University Campuses. In IEEE International Smart Cities Conference (ISC2) (pp. 1–5). Trento, Italy: IEEE.
Abstract: A new method to perform a bottom-up extraction and benchmark of the perceived multilevel smartness of complex ecosystems has been recently described and applied to territories and learning ecosystems like university campuses and schools. In this paper we study the resilience of our method by comparing and integrating the data collected in several European Campuses during two different academic years, 2014-15 and 2015-16. The overall results are: a) a more adequate and robust definition of the orthogonal multidimensional space of representation of the smartness, and b) the definition of a procedure to identify data that exhibits a limited level of trust.
Appears in Collections:1. RAGE Publications

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