Pilot campaign for a one-week collection of multimodal journeys by the UPC community using the MobilitApp tool


In collaboration with UPC Sostenible, the SISCOM group is organizing a one-week campaign to collect mobility trips to and from the campus. The aim is to analyze the mobility habits of our community to better promote measures to achieve more sustainable mobility at UPC.

Developed by the SISCOM group, the mobile application  MobilitApp  predicts the mode of transport used during travel. Available for Android and soon also fo IoS. The objective is to help analyze the mobility habits of citizens to improve public transport and promote sustainable mobility.

MobilitApp periodically collects data from 3 mobile sensors: accelerometer, magnetometer and gyroscope. The information obtained is processed to train a machine learning model capable of subsequently predicting the means of transportation used by citizens. Currently, MobilitApp recognizes these means of transport with more than 88% accuracy: bicycle, electric bicycle, electric scooter, bus, underground, train, tram, motorcycle, car, running and walking.

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