Introducing the MIE Lab's Human Mobility Analysis Framework trackintel01. May 2019
We are very excited to announce that we started development of an open source framework to process and analyze human mobility data, based on GPS recordings. In our research, we frequently stumbled upon the need to quickly perform various preprocessing and analysis tasks on GPS data. These include segmentation, transport mode detection, map matching, extraction of metrics for various transport modes (average daily distance, duration, etc.), staypoint detection, but also mobility prediction, generation of alternative transport routes, assessment and classification of behavior, context augmentation, and many more.
While our first efforts target the most basic preprocessing and analysis steps, we will continuously add results and algorithms from our most cutting-edge research on the processing of mobility data. You can find the library in the MIE Lab's GitHub repository.