Investigating MIDR through AI: a case study of the city of Most in Czech Republic
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 highlighte...
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| Format: | Article |
| Language: | English |
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CTU Central Library
2024-03-01
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| Series: | Acta Polytechnica CTU Proceedings |
| Subjects: | |
| Online Access: | https://ojs.cvut.cz/ojs/index.php/APP/article/view/9635 |
| _version_ | 1797218183413760000 |
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| author | Akshatha Ravi Kumar Noor Marji Gülbahar Emir Isik Lijun Chen |
| author_facet | Akshatha Ravi Kumar Noor Marji Gülbahar Emir Isik Lijun Chen |
| author_sort | Akshatha Ravi Kumar |
| collection | DOAJ |
| description |
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.
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| first_indexed | 2024-04-24T12:13:42Z |
| format | Article |
| id | doaj.art-887adeea77654b81acf3bf75e369bbd6 |
| institution | Directory Open Access Journal |
| issn | 2336-5382 |
| language | English |
| last_indexed | 2024-04-24T12:13:42Z |
| publishDate | 2024-03-01 |
| publisher | CTU Central Library |
| record_format | Article |
| series | Acta Polytechnica CTU Proceedings |
| spelling | doaj.art-887adeea77654b81acf3bf75e369bbd62024-04-08T09:12:00ZengCTU Central LibraryActa Polytechnica CTU Proceedings2336-53822024-03-014610.14311/APP.2024.46.0040Investigating MIDR through AI: a case study of the city of Most in Czech RepublicAkshatha Ravi Kumar0Noor Marji1Gülbahar Emir Isik2Lijun Chen3Czech Technical University in Prague, Faculty of Architecture, Jugoslávských partyzánů 1580/3, 160 00 Prague 6 – Dejvice, Czech RepublicCzech Technical University in Prague, Faculty of Architecture, Jugoslávských partyzánů 1580/3, 160 00 Prague 6 – Dejvice, Czech RepublicCzech Technical University in Prague, Faculty of Architecture, Jugoslávských partyzánů 1580/3, 160 00 Prague 6 – Dejvice, Czech RepublicCzech Technical University in Prague, Faculty of Architecture, Jugoslávských partyzánů 1580/3, 160 00 Prague 6 – Dejvice, Czech Republic 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. https://ojs.cvut.cz/ojs/index.php/APP/article/view/9635mining-induced displacement and resettlementartificial intelligencerelocationMost cityurban planning |
| spellingShingle | Akshatha Ravi Kumar Noor Marji Gülbahar Emir Isik Lijun Chen Investigating MIDR through AI: a case study of the city of Most in Czech Republic Acta Polytechnica CTU Proceedings mining-induced displacement and resettlement artificial intelligence relocation Most city urban planning |
| title | Investigating MIDR through AI: a case study of the city of Most in Czech Republic |
| title_full | Investigating MIDR through AI: a case study of the city of Most in Czech Republic |
| title_fullStr | Investigating MIDR through AI: a case study of the city of Most in Czech Republic |
| title_full_unstemmed | Investigating MIDR through AI: a case study of the city of Most in Czech Republic |
| title_short | Investigating MIDR through AI: a case study of the city of Most in Czech Republic |
| title_sort | investigating midr through ai a case study of the city of most in czech republic |
| topic | mining-induced displacement and resettlement artificial intelligence relocation Most city urban planning |
| url | https://ojs.cvut.cz/ojs/index.php/APP/article/view/9635 |
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