Abstract
The need of citizens engagement in modeling the vast amount of services provided by governments has led to mechanisms where people are seen as sensors. Development policies, processes, and aims are evolving regarding urban planning in order to use citizens-generated data as input in the intelligent systems. This data may be a rich source to mine citizens’ current requirements, detect serious problems in a city and determine what is urgent and what is not. Citizens as sensors is a new paradigm that transforms the idea of efficiency implemented in a “smart city” into the notion of resilience oriented to “cognitive cities”. In this regard, a systematic literature review of how intelligent systems have been employed towards modeling cognition in urban planning was conducted. This work propose a classification on how intelligent systems are being approached: Implementations in intelligent governance, big data and analytic solutions, fuzzy methods, and application scenarios toward cognitive urban planning. Moreover, this study details a comparison of the approaches mentioned above in terms of technology targeted and/or computing methods employed, as well as the advantages of the proposed works and their limitations. The results of the present review revealed that previous studies contributed with combined strategies that apply soft computing methods, but the implementation of empirical validations has not been studied in depth.
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Recalde, L., Meza, J., Terán, L. (2020). Cognitive Systems for Urban Planning: A Literature Review. In: Santos, H., Pereira, G., Budde, M., Lopes, S., Nikolic, P. (eds) Science and Technologies for Smart Cities. SmartCity 360 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-030-51005-3_22
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