Smart Cities, Big Data, and Communities: Reasoning From the Viewpoint of Attractors

In what sense is a city smart? There are established entities defining this rich area of cross-disciplinary studies, and they refer to social, technical, economic, and political factors that keep evolving, thus offering opportunities for constant refinement of the concept of smart city. The emerging properties are mostly contextual, and affect urban data types and their capacity to form complex information systems. A well-known problem in computational analysis is the integration of lot of generated data. The heterogeneity and diversity of smart city data sources suggest that a system’s approach could be ideal to assemble drivers of multiple forces and dynamics, suggesting adaptive solutions too. However, the nature of such systems is quite unpredictable and chaotic, leading to the natural aim of stabilizing them. Studies have proposed methods based on various criteria, say parametric, entropic, anthropic etc. As many factors and variables underlie the system’s drivers, attractors derived from dynamical systems are proposed to describe smart city contexts through the various interlinked big data and networks.