Electronic shepherd - a low-cost, low-bandwidth, wireless network system
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Hardware design experiences in ZebraNet
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Accuracy characterization for metropolitan-scale Wi-Fi localization
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Canopy closure estimates with GreenOrbs: sustainable sensing in the forest
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Towards mobile phone localization without war-driving
INFOCOM'10 Proceedings of the 29th conference on Information communications
Beyond trilateration: on the localizability of wireless ad hoc networks
IEEE/ACM Transactions on Networking (TON)
No need to war-drive: unsupervised indoor localization
Proceedings of the 10th international conference on Mobile systems, applications, and services
Localization of wireless sensor networks in the wild: pursuit of ranging quality
IEEE/ACM Transactions on Networking (TON)
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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.