Jakovits, Pelle, juhendajaMägi, Hanna MariaTartu Ülikool. Loodus- ja täppisteaduste valdkondTartu Ülikool. Arvutiteaduse instituut2025-10-202025-10-202025https://hdl.handle.net/10062/116871This thesis analyzes bus delays in the city of Tartu during the years 2019–2024. The aim of the study was to evaluate how accurately predicted arrival times reflect actual arrival times and to identify problematic routes, time periods, and stops in terms of schedule adherence. The dataset was obtained from the Cumulocity platform and processed using Python. The results show that, for certain routes and time periods, actual delays deviate significantly from predictions. A cleaned and structured dataset was also created as part of the work, which can be used for future developments and urban planning by the city.ethttps://creativecommons.org/licenses/by-nc-nd/4.0/ÜhistransportbusshilinemineIoTandmeanalüüsTartuCumulocityGTFSbakalaureusetöödinformaatikainfotehnoloogiainformaticsinfotechnologyThesis