Investigating MIDR through AI: a case study of the city of Most in Czech Republic

Abstract

Urban planning, which is inherently multifaceted, requires the development of innovative tools to navigate its complexities. This study introduces a pioneering approach that presents an AI-driven framework tailored for urban data collection and analysis. The impetus for this framework is highlighted through the unique narrative of Most city, which is profoundly transformed by mininginduced displacement and resettlement. While most cities serve as a vivid illustration of the challenges cities can face, especially in the wake of industrial imperatives, this study focuses on the potential of AI in addressing such challenges. The proposed framework, while grounded in advanced computational methodologies, is designed with keen emphasis on real-world applications, ensuring its relevance and adaptability. By integrating Most city’s detailed account with this AI-centric methodology, this study emphasizes the importance of a data-driven approach in understanding and addressing urban dilemmas. Importantly, this study is preparatory, laying the groundwork for the framework’s future application, especially in contexts such as Most city. By bridging advanced AI techniques with tangible urban challenges, this research illuminates a path forward, suggesting a future in which urban planning is not only informed by data but also empowered by AI’s analytical process.