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|Title:||A Study of the Interaction of Human Smart Characteristics with Demographic Dynamics and Built Environment: The Case of Limassol, Cyprus||Authors:||Alverti, Maroula N.
Hadjimitsis, Diofantos G.
|Major Field of Science:||Engineering and Technology||Field Category:||Civil Engineering||Keywords:||Human-centered smart cities;Dispersed urbanization;Urban challenges;Local determinants;Urban planning;Limassol||Issue Date:||Mar-2020||Source:||Smart Cities, 2020, vol 3, no. 1, pp. 48-73||Volume:||3||Issue:||1||Start page:||48||End page:||73||Project:||ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment||Journal:||Smart Cities||Abstract:||The smart city notion provides an integrated and systematic answer to challenges facing cities today. Smart city policy makers and technology vendors are increasingly stating their interest in human-centered smart cities. On the other hand, in many studies smart city policies bring forward a one-size-fits-all type of recommendation for all areas in question instead of location-specific ones. Based on the above considerations, this paper illustrates that smart citizen characteristics, alongside local urban challenges, are paving the way towards more e ective e orts in smart city policy decision making. Our main presumption is that the development level of human-centered indicators of smart cities varies locally. The scientific objective of this paper is to find a simple, understandable link between human smart characteristics and local determinants in Limassol city, Cyprus. The data set consists of seven indicators defined as human smart characteristics and seven which determine local urban challenges consisting of demographic dynamics and built infrastructure attributes based on housing. Correlations of the 14 above indicators are examined in entirety and separately, as the study area was divided into three spatial sub-groups (high, moderate, and low coverage areas) depending on dispersed urbanization, as the main challenge of the study area. The data were obtained mainly from the most recent population census in 2011 and categorized in sub-groups by triggering CLC 2012. Analyzing the statistics using principal component analysis (PCA), we identify significant relationships between human smart city characteristics, demographic dynamics and built infrastructure attributes which can be used in local policy decision making. Spatial variations based on the dispersed urbanization are also observed regarding the above-mentioned relationships.||Description:||The authors also would like to acknowledge the “CUT Open Access Author Fund” for covering the open access publication fees of the paper.||URI:||https://ktisis.cut.ac.cy/handle/10488/18889||ISSN:||2624-6511||DOI:||10.3390/smartcities3010004||Rights:||© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
Attribution-NonCommercial-NoDerivatives 4.0 International
|Type:||Article||Affiliation :||Cyprus University of Technology
ERATOSTHENES Centre of Excellence
|Appears in Collections:||Publications under the auspices of the EXCELSIOR H2020 Teaming Project/ERATOSTHENES Centre of Excellence|
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