Urban Data Analytics involves using advanced analytical techniques, including machine learning and artificial intelligence, to gain insights from data generated by cities and their inhabitants. This data can include everything from traffic patterns and air quality to crime rates and energy consumption. By analyzing and visualizing this data, we can gain a deeper understanding of the complex systems that make up cities, identify patterns and trends, and make more informed decisions that improve quality of life for residents. In our GitHub repo, we showcase various urban data analytic examples, from predicting traffic congestion to optimizing energy consumption in buildings. We hope that these examples inspire others to leverage the power of data and AI to create smarter, more sustainable, and more livable cities.
DKSR-Data-Competence-for-Cities-Regions/Urban-Data-Analytics
Folders and files
| Name | Name | Last commit date | ||
|---|---|---|---|---|