Flores, Huber, juhendajaRaza, AliTartu Ülikool. Loodus- ja täppisteaduste valdkondTartu Ülikool. Arvutiteaduse instituut2023-09-282023-09-282021https://hdl.handle.net/10062/93203Human mobility research is gaining traction, opening up new avenues for research in smart cities infrastructure development. Human mobility can reveal information regarding population dispersion across a large area, human behaviour, and individuals’ daily routines. In the meantime, individual mobility is intensively investigated, but group mobility is mostly unexplored. In this thesis, we developed user trajectories based on the dataset collected from their cellular network connectivity. We develop a method for assessing group mobility by examining the similarity in users’ trajectories between locations in different users’ routines. Our results indicate that while multiple groups can be formed in specific locations (in a static manner), it is difficult to find users that share the same spatial and temporal characteristics while moving.engopenAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalgroup mobilitydevice-to-device communicationopportunistic d2d collaborationshuman mobilitymobile crowdsensingmagistritöödinformaatikainfotehnoloogiainformaticsinfotechnologyThesis