Voting-Based Intervention Planning Using AI-Generated Images

Abstract

The continuous evolution of artificial intelligence and advanced algorithms capable of generating information from simplified input creates new opportunities for several scientific fields. Currently, the applicability of such technologies is limited to art and medical domains, but it can be applied to engineering domains to help the architects and urban planners design environmentally friendly solutions by proposing several alternatives in a short time. This work utilizes the image-inpainting algorithm for suggesting several alternative solutions to four European cities. In addition, this work suggests the utilization of a voting-based framework for finding the most preferred solution for each case study. The voting-based framework involves the participation of citizens and, as a result, decentralizes and democratizes the urban planning process. Finally, this research indicates the importance of deploying generative models in engineering applications by proving that generative AI models are capable of supporting the architects and urban planners in urban planning procedures.