Open Access Journal

ISSN: 2183-7635

Article | Open Access | Ahead of Print | Last Modified: 18 September 2024

From Vision to Reality: The Use of Artificial Intelligence in Different Urban Planning Phases

Full Text   PDF (free download)
Views: 2802 | Downloads: 1563


Abstract:  In an urban context, the use of artificial intelligence (AI) can help to categorise and analyse large amounts of data quickly and efficiently. The AI approach can make municipal administration and planning processes more efficient, improve environmental and living conditions (e.g., air quality, inventory of road damages, etc.), or strengthen the participation of residents in decision-making processes. The key to this is “machine learning” that has the ability to recognise patterns, capture models, and learn on the basis of big data via the application of automated statistical methods. However, what does this mean for urban planning and the future development of cities? Will AI take over the planning and design of our cities and actively intervene in and influence planning activities? This article applies a systematic literature review supplemented by case study analyses and expert interviews to categorise various types of AI and relate their potential applications to the different phases of the planning process. The findings emphasize that AI systems are highly specialised applications for solving and processing specific challenges and tasks within a planning process. This can improve planning processes and results, but ultimately AI only suggests alternatives and possible solutions. Thus, AI has to be regarded as a planning tool rather than the planning solution. Ultimately, it is the planners who have to make decisions about the future development of cities, taking into account the possibilities and limitations of the AI applications that have been used in the planning process.

Keywords:  artificial intelligence; decision-making; digital participation; planning phases; smart city; urban planning

Published:   Ahead of Print


DOI: https://doi.org/10.17645/up.8576


© Frank Othengrafen, Lars Sievers, Eva Reinecke. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.