KEYWORD |
Transport Research for Innovation and Sustainability (TRIS)
Develop a mobile app application to collect mobility patterns and transport supply (also using bus GTFS, bus line information and GPS).
Thesis in external company
keywords AUTOMATED PASSENGER COUNTING, DATA COLLECTION, GPS, GTFS, IOT AND SENSORS, LOCALISATION METHODS, MOBILE APPLICATIONS, PUBLIC TRANSPORT
Reference persons CRISTINA PRONELLO
Research Groups Transport Research for Innovation and Sustainability (TRIS)
Thesis type EXPERIMENTAL - DESIGN
Description Collection of mobility patterns as well as passenger counting within public transport systems uses various methods. The problem with all automatic methods is that they do not have high accuracy. To improve them through the development of algorithms, it is necessary to carry out travel surveys through questionnaires and manual counting campaigns that are time-consuming and expensive. A very useful support would be to develop a mobile app that supports data collection and makes it more accurate than a purely manual count.
The student will have to develop a smartphone application that facilitates and optimise the mobility data collection and manual counting of passengers.
Required skills Programming knowledge especially in Python, some knowledge of C will be beneficial but not mandatory. Knowledge on mobile app development.
Deadline 05/11/2024
PROPONI LA TUA CANDIDATURA