Mining raw GPS readings for deep profiling of location contexts - part I

• Main Author: Lim, Qing Chuan
• Other Authors: Luo Jun
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering
• Online Access: https://hdl.handle.net/10356/181403
• Institution: Nanyang Technological University

The Global Navigation Satellite System (GNSS) is a satellite-based system that provides global positioning, navigation and timing information to receivers enabling accurate geolocation anywhere on earth. However there are many environmental contexts within which this data is interfered with and rendered inaccurate. The mining of Raw GNSS data has been made available to the public as of Android 7.0 which opens up the possibility for noise and environmental contexts to be taken into consideration and processed out of the transmission, enabling a more accurate location prediction. This thesis focuses on automating the labeling of environmental contexts to address the large amount of time needed to label all potential environmental contexts that exist. It hoped that this will support future research attempts at identifying environmental contexts of GNSS receivers.