Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities

Abstract

Wide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the influence of the emergence of these tools on the design and planning of the cities in the context of urban change. In this paper, the implications of the application of artificial-intelligence-based tools and geo-localised big data, both in solving specific research problems in the field of urban planning and design as well as on planning practice, are discussed. The paper is concluded with both cognitive conclusions and recommendations for planning practice. It is directed towards urban planners interested in the emerging urban big data analytics based on AI-related tools and towards urban theorists working on new methods of describing urban change.

Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review

“…In recent years, the rise of Big Data and computing power has empowered AI, and its new generation is rapidly expanding and becoming “an attractive topic for research” (Duan et al 2019 ). As consistent with the findings for the second and third periods, ANN, Deep Neural Network (DNN), SVM, GA, LR, and DT are among the prominent AI techniques that gained strong traction in recent years (Şerban and Lytras 2020 ; Shrestha and Mahmood 2019 ), so are ML, DL, and cognitive AI models in relation to the planning and development of smart cities (Kamrowska-Załuska 2021 ; Şerban and Lytras 2020 ). Similarly, AI has empowered the analysis of the vast troves of data generated via the IoT infrastructure in smart cities.…”

Greencoin as an AI-Based Solution Shaping Climate Awareness

“…Thus, many researchers worldwide are seeking solutions to improve the quality of urban commuting systems at the governance level. Kamrowska-Załuska found [ 54 ] that they are mostly focused on urban traffic analyses, the capacity of transport networks, commuting corridors, and energy planning models.…”

“…As found by Kamrowska-Załuska [ 54 ], self-organizing mechanisms can help to achieve sustainability and allow the evaluation of dynamic attributes on the spatiotemporal scale, namely the preferences, emotions, and satisfaction of individuals. They further allow indirect participation with a new type of analysis based on specific behavioral patterns and as such can provide more reasonable and accurate explanations for the evolution of the mechanisms of complex systems.…”

“…An overview of AI applications in cities provides valuable information for optimizing living conditions in the urban environment following sustainable social, economic, and environmental development [ 23 , 54 , 98 ]. The number of case studies found proved the increasing interest in the use of AI for urban processes [ 25 ], but our SLR search [ 9 , 10 , 11 ] showed that despite the recognized need to develop digital solutions to achieve urban climate neutrality [ 5 ], there is still limited evidence on tools that moved outside the theoretical or pilot phase.…”

“…The methodological approach is based on Kamrowska-Załuska’s study [ 54 ] evaluating the potential of AI-based solutions in urban planning. We narrowed down the study to the educational aspects of a smart city.…”