The URBAN AI GUIDE aids city leaders and urban technologists (academic, public, private, and community-focused) in better understanding how artificial intelligence operates in urban contexts.
The idea for this guide arose from conversations with city leaders, who were confronted with new technologies, like artificial intelligence, as a means of solving complex urban problems, but who felt they lacked the background knowledge to properly engage with and evaluate the solutions. In some instances, this knowledge gap produced a barrier to project implementation or led to unintended project outcomes.
The guide begins with a literature review, presenting the state of the art in research on urban artificial intelligence. It then diagrams and describes an "urban AI anatomy," outlining and explaining the components that make up an urban AI system. Insights from experts in the Urban AI community enrich this section, illuminating considerations involved in each component. Finally, the guide concludes with an in-depth examination of three case studies: water meter lifecycle in Winnipeg, Canada, curb digitization and planning in Los Angeles, USA, and air quality monitoring in Vilnius, Lithuania. Collectively, the case studies highlight the diversity of ways in which artificial intelligence can be operationalized in urban contexts, as well as the steps and requirements necessary to implement an urban AI project.
Since the field of urban AI is constantly evolving, we anticipate updating the guide annually. Please consider filling out the contribution form, if you have an urban AI use case that has been operationalized. We may contact you to include the use case as a case study in a future edition of the guide.
As a continuation of the guide, we offer customized workshops on urban AI, oriented toward municipalities and other urban stakeholders, who are interested in learning more about how artificial intelligence interacts in urban environments. Please contact us if you would like more information on this program.
Recommended Citation: Popelka, S., Narvaez Zertuche, L., Beroche, H. (2023). Urban AI Guide. Urban AI. DOI: 10.5281/zenodo.7708833
