Using Artificial Intelligence for Better City Planning
To support the eThekwini municipality in automating their building mapping process, the UNITAC team developed BEAM, a software that uses Machine Learning to radically accelerate the spatial recognition of buildings and keep track of changes in the built-up area or density. BEAM (Building & Establishment Automated Mapper) is an open source and easy-to-use tool that allows the user to quickly detect and visualise rooftops in a specific area by simply uploading aerial images of a given location.
How Knowledge Graphs can help analysing risk and resilience in cities
UNITAC Hamburg created the City Resilience Tool. A model, that through the use of knowledge graphs can help analyse risks and improve the resilience of urban systems by providing cities with information on potential shocks, vulnerabilities and stresses.
Experimenting with data for urban planning in the city of Maceió, Brazil
Read the full article with the main findings derived from the research into relevant tools for better data collection and management in the city of Maceió. A case study and pilot tool to demonstrate how open data can be used for public policy and decision making processes in also included.