AI-Assisted Analysis and Evaluation of Urban Public Spaces

Professor Introduction

Isaac | Ph.D. in  Architecture

Home Institute：Tohoku University (Japan)

Project Description

Urban public spaces are integral to our lives, embodying the interplay between "man-made spaces shaping people and people shaping spaces." These spaces not only provide essential venues for social life and activities but also act as incubators and generators of social interactions, enriching our lives and enhancing the city's image. Therefore, evaluating and improving the quality of urban public spaces is crucial for enhancing public life and urban quality.

Traditional design processes often involve superficial site surveys, lacking in-depth investigation of the site and its surroundings, as well as the current state and needs of public life. This results in lavishly constructed spaces that are underutilized and fail to meet public demands.

This project aims to leverage AI tools, particularly ChatGPT, to assist in the faster and more accurate evaluation and application of urban public spaces. Students will learn cutting-edge AI applications and gain a deeper understanding of their living spaces and the events occurring within them.

Project Keywords

Project Outline

Part 1 : Introduction to Urban Public Spaces
• Definition and importance of urban public spaces
• The role of public spaces in human social life
• Impact of public spaces on urban image

Part 2: Traditional Methods of Public Space Evaluation
• Overview of traditional evaluation methods
• Limitations of site surveys and questionnaires
• Transition from big data to multidimensional data analysis

Part 3:  AI Applications in Urban Space Evaluation
• Basics of artificial intelligence and its applications in architecture
• Overview of AI tools like ChatGPT
• How AI enhances the efficiency and accuracy of public space evaluation

Part 4:  AI-Assisted Public Space Evaluation Methods
• Methodology for integrating AI tools in public space evaluation
• Case studies of AI applications in urban space analysis

• Data collection and analysis using AI tools

Part 5:  Practical Applications and Case Studies
• Real-world examples of AI-assisted public space evaluation
• Comparative analysis of traditional and AI-assisted evaluations
• Success stories and best practices

Part 6: Development of Evaluation Standards and Indicators
• Establishing clear and measurable evaluation standards
• Identifying key indicators of public space quality
• Using AI tools to optimize and validate these standards and indicators

Part 7:  Future Directions and Impact
• Potential advancements in AI for urban space evaluation
• Long-term impacts on urban planning and public space design
• Opportunities for student-led research and innovation

Part 8: Data Analysis and Interpretation
• Utilizing bioinformatics tools for experimental data analysis
• Identifying key genes and pathways affected by gene editing

Part 9: Development of Potential Therapeutic Strategies
• Exploring the feasibility of translating gene editing findings into clinical applications
• Evaluating the benefits and challenges of proposed therapeutic strategies

Part 10: Potential Applications in CML Treatment
• Discussing the therapeutic potential of identified targets
• Evaluating the benefits and challenges of implementing these strategies in clinical settings

Part 11: Results and Discussion
• Presenting experimental and computational results
• Discussing the significance and potential applications of the research findings
• Comparing new therapeutic targets with existing CML treatments

Part 12: Conclusion and Future Research Directions
• Summarizing key findings and their importance
• Identifying research limitations and suggesting future research directions
• Proposing practical applications of gene editing in various fields

Part 13: Reporting and Presentation
• Writing a comprehensive research report with clear structure, concise language, and accurate data presentation
• Preparing and delivering an engaging oral presentation of the research background, methods, results, and conclusions

Suitable for

High School Students:  
•  Interested in architecture, urban design, and AI applications, preparing for advanced studies or competitions
• Basic knowledge of architecture, urban planning, and computer science

University Students:
• Majoring in architecture, urban design, or related fields, seeking to deepen understanding and engage in research
• Familiar with basic architectural design and evaluation methods, with some programming and data analysis skills