In July 2022, an AirView Car was driven in and around Augsburg to take air quality measurements a part of a European EXPANSE Project. The car was further equipped with a Go Pro camera and took panoramic images throughout the campaign.

By analysing the images taken during the campaign, it is possible to extract site-specific characteristics such as vegetation percentage, Sky View Factor and building materials. Such information is valuable to better understand the interactions between air quality and the urban environment.

The project will require the identification of objects such as vehicles, pedestrians, vegetation as well as urban morphological parameters using established machine learning techniques. Given the large data volume, computationally efficient processing and visualisation will be an essential part of the project.

Prerequisites: 

The student should have experience in using Machine or Deep learning frameworks. Furthermore, experience with Python or R will be advantageous. The project is aimed at Bachelor's or Master's in medical informatic or similar fields. The project duration will be 6 – 8 weeks for Bachelor students and 13 – 15 weeks for Master students.

If you are interested in this research project or would like to find out more, please contact Prof. Dr. Christoph Knote or Dr. Bin Zhou