2013/08/31 by Bo Cheng, Bo, Cheng, Xiangyang Li +5
Computer Science · Engineering · Social Sciences · #Computers and Society (cs.CY) #Context-Aware Activity Recognition Systems #FOS: Computer and information sciences #FOS: Electrical engineering #Human Mobility and Location-Based Analysis #Indoor and Outdoor Localization Technologies #Networking and Internet Architecture (cs.NI) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1310.8187
openalex publication_date 2013/08/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present SmartLoc, a localization system to estimate the location and the traveling distance by leveraging the lower-power inertial sensors embedded in smartphones as a supplementary to GPS. To minimize the negative impact of sensor noises, SmartLoc exploits the intermittent strong GPS signals and uses the linear regression to build a prediction model which is based on the trace estimated from inertial sensors and the one computed from the GPS. Furthermore, we utilize landmarks (e.g., bridge, traffic lights) detected automatically and special driving patterns (e.g., turning, uphill, and downhill) from inertial sensory data to improve the localization accuracy when the GPS signal is weak. Our evaluations of SmartLoc in the city demonstrates its technique viability and significant localization accuracy improvement compared with GPS and other approaches: the error is approximately 20m for 90% of time while the known mean error of GPS is 42.22m.