Hadachi, Amnir, juhendajaKüüsvek, MariaTartu Ülikool. Loodus- ja täppisteaduste valdkondTartu Ülikool. Arvutiteaduse instituut2023-10-262023-10-262023https://hdl.handle.net/10062/93759This thesis explores creating a tool to support the displayed information in the existing ITS lab Modal Split dashboard, which uses data from sensors around Tartu City to produce a modal split estimation of various traffic types (Vehicle, Bike, Pedestrian). This thesis aims to incorporate sensor monitoring to facilitate data quality assessment into Modal Split and in turn, improve the overall quality of Modal Split. This solution comes in the form of an interactive dashboard, which allows users to view the welfare of sensors for multiple dates and filter sensors by type. The finished sensor monitoring dashboard includes a heatmap that displays assessment by the sensor and by the hour for twenty-four hours. In addition, it provides a daily summary of each sensor’s welfare in the form of a heatmap. The dashboard can generate a line graph that displays the number of events for a sensor of the user's choosing by the hour. In addition, a map visualisation is also included that highlights the location of a particular sensor to make it easy to identify its location. The dashboard is designed to make it easy for users to identify problems with sensors in the ITS lab system, and thus contribute to the overall quality of the Modal Split dashboard.engopenAccessAttribution-NonCommercial-NoDerivatives 4.0 InternationalIoTMonitoringCumulocityPythonDashMariaDBbakalaureusetöödinformaatikainfotehnoloogiainformaticsinfotechnologyThesis