Stop Detection and Location Accuracy Improvement in Mobile Positioning
Name
Tanel Kiis
Abstract
Mobile operators collect data about their clients' activity in the mobile network. Each event made in the mobile network has reference to the antenna the mobile device was connected to at that time. By knowing the coverage areas of the antennas the peoples' trajectories throughout the day can be approximated. Its spatial coarseness and temporal sparseness makes extracting information from this data a compelling task requiring specially crafted algorithmic tools. Detecting when and where did the mobile device stopped is a crucial step that serves as a basis for subsequent data analysis tasks on this data. Here a state of the art stop detection algorithm is analysed and some shortcomings of it identified. The proposed improvements to these have been shown to improve the performance of the stop detection algorithm significantly. Additionally, the possibility of improving the location accuracy by incorporating periodicity into the movement models is investigated.
Graduation Thesis language
English
Graduation Thesis type
Master - Computer Science
Supervisor(s)
Toivo Vajakas
Defence year
2018