Evaluating the Resilience of the Bottom-up Method used to Detect and Benchmark the Smartness of University Campuses

Carlo Giovannella, Diana Andone, Mihai Dascalu, Elvira Popescu, Matthias Rehm, Oscar Mealha

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

9 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationProceedings of the IEEE Second International Smart Cities Conference : Improving the citizens quality of life
PublisherIEEE Computer Society Press
Publication date2016
ISBN (Print)978-1-5090-1847-5
ISBN (Electronic)978-1-5090-1846-8
DOIs
Publication statusPublished - 2016
EventIEEE International Smart Cities Conference (ISC2 2016) - Trento, Italy
Duration: 12 Sept 201615 Sept 2016
http://events.unitn.it/en/isc2-2016

Conference

ConferenceIEEE International Smart Cities Conference (ISC2 2016)
Country/TerritoryItaly
CityTrento
Period12/09/201615/09/2016
Internet address

Keywords

  • Smart city learning
  • Learning Analytics

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