Characterizing Human Mobility Patterns in Saudi Arabia Using Cellular Data
dc.contributor.advisor | Ivica, Kostanic | |
dc.contributor.author | Alnefaie, Meshal Musharraf E | |
dc.date.accessioned | 2025-06-17T20:33:30Z | |
dc.date.issued | 2025-05 | |
dc.description.abstract | The study analyzes human mobility in Saudi Arabia. Using crowd-source data, Riyadh mobility is analyzed to find trends and highlight mobility patterns of individuals in Riyadh. Then, the mobility of Riyadh is compared with that of Jeddah and Dammam in a similar data collection and analysis. Four mobility metrics are utilized: Number of Visited Locations (N LOC ), Number of Unique Locations (N ULOC ), Radius of Gyration (R GYR ), and Distance Traveled (D TRV ). The results show interesting outcomes about individuals in the three cities. Although these cities are far from each other, they observe the same mobility patterns. These findings have the potential to help policymakers understand how people move around these cities. | |
dc.format.extent | 136 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14154/75579 | |
dc.language.iso | en_US | |
dc.publisher | Florida Institute of Technology | |
dc.subject | Data mining | |
dc.subject | Electrical engineering | |
dc.subject | Human mobility | |
dc.subject | Big data | |
dc.subject | Wireless | |
dc.subject | Cellular data | |
dc.title | Characterizing Human Mobility Patterns in Saudi Arabia Using Cellular Data | |
dc.type | Thesis | |
sdl.degree.department | Electrical Engineering and Computer Science | |
sdl.degree.discipline | and Computer Science | |
sdl.degree.grantor | Florida Institute of Technology | |
sdl.degree.name | Doctor of Philosophy |