Study level

  • PhD
  • Master of Philosophy
  • Honours
  • Vacation research experience scheme

Faculty/School

Faculty of Engineering

School of Architecture and Built Environment

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Professor Tan Yigitcanlar
Position
Professor
Division / Faculty
Faculty of Engineering

External supervisors

  • Raveena Pelige

Overview

Advances in artificial intelligence (AI) offer urban planning practice many novel prospects. By the responsive use of AI, planners can effectively analyse data, improve processes, increase efficiency, and prioritise human-centric aspects of planning to develop sustainable cities. Computer vision is one of the key areas where responsible AI is applied in urban planning to revolutionise the analysis and interpretation of visual data, like images and videos captured in cities to aid decision and plan making processes. While the potential impacts of the adoption of AI technology are widespread, they may not always be beneficial if urban planners lack a sound understanding of its limitations, challenges, and ethical considerations. This brings the need for research into responsible computer vision for urban planning.

References

Yigitcanlar, T., Corchado, J., Mehmood, R., Li, R., Mossberger, K., & Desouza, K. (2021). https://doi.org/10.3390/joitmc7010071Responsible urban innovation with local government artificial intelligence (AI): a conceptual framework and research agenda. Journal of Open Innovation: Technology, Market, and Complexity, 7, 71.

Son, T., Weedon, Z., Yigitcanlar, T., Sanchez, T., Corchado, J., & Mehmood, R. (2023). Algorithmic urban planning for smart and sustainable development: Systematic review of the literature. Sustainable Cities and Society, 94, 104562.

Research activities

This project will investigate the responsible deployment of AI technologies particularly, computer vision applications in urban planning. As part of the research project, you will carry out the following tasks (by using desktop research and web scraping techniques):

  • Explore the current status of computer vision applications for urban planning in Australia
  • Investigate the key elements or factors that should be considered when developing and deploying responsible AI technologies, particularly computer vision applications, in urban planning
  • Collect and analyse the perceptions of urban planning practitioners and communities regarding AI applications, particularly computer vision applications, in urban planning
  • Present the findings in a concise report and poster formats

Outcomes

The outcomes of this work will include:

  • A concise project report on the above research activities
  • A digital poster presenting the methodology and key findings

Skills and experience

  • data collection skills
  • analytical ability
  • problem-solving skills
  • adequate methodological background
  • broad understanding of urban planning technologies
  • ambition to complete a research project within a given time frame

Keywords

Contact

Contact the supervisor for more information.