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    Generative AI models can assist architects and urban planners in creating eco-friendly urban designs. This study uses AI image inpainting and a citizen voting framework to democratize urban planning for European cities.

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    Area of Science:

    • Engineering
    • Urban Planning
    • Artificial Intelligence

    Background:

    • Artificial intelligence (AI) and advanced algorithms offer new possibilities across scientific fields.
    • Current AI applications are mainly in art and medicine, with untapped potential in engineering.
    • AI can support architects and urban planners in designing sustainable urban environments.

    Purpose of the Study:

    • To explore the application of AI, specifically image inpainting, in generating alternative urban design solutions.
    • To introduce a citizen-involved voting framework for selecting preferred urban plans.
    • To demonstrate the value of generative AI in engineering and urban planning.

    Main Methods:

    • Utilized an image-inpainting algorithm to generate design alternatives for four European cities.
    • Implemented a voting-based framework to facilitate the selection of the most suitable urban plan.
    • Involved citizens in the decision-making process to decentralize urban planning.

    Main Results:

    • The study successfully generated multiple design alternatives for urban environments using AI.
    • The voting framework enabled a democratic selection process for urban planning solutions.
    • Generative AI proved effective in supporting architects and urban planners.

    Conclusions:

    • Generative AI models are valuable tools for architects and urban planners.
    • AI can significantly aid in designing environmentally friendly urban solutions.
    • Citizen participation through voting frameworks enhances the urban planning process.