Shih-Yung Juan
ABSTRACT
Over the past few years, personal sensing applications, such as travel path sharing and location recording, have been more and more popular. These applications use GPS sensors to record track points on smartphones and upload the track points to clouds in real time for information sharing. However, uploading a lot of GPS points may lead to heavy network traffic and much higher power consumption. To address the problem, we present corner extraction by GPS filtering (CEGF) that extracts corner feature GPS points (CFGPs) from GPS track points (GTPs). Applications only need to upload the CFGPs to save the uploading energy on smartphones. CFGPs can be regarded as characteristic points of corners to represent the corresponding roads. To reduce the number of uploaded points, we use CEGF to filter out the CFGPs from a large amount of GTPs.
- Liu et al., "Energy efficient GPS sensing with cloud offloading." In Proc. 10th ACM Conf. Embed. Network Sensor Sys. (SenSys '12), Nov. 2012. Google Scholar
Digital Library
- Ester et al., "A density-based algorithm for discovering clusters in large spatial databases with noise". In Proc. of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Aug. 1996.Google ScholarDigital Library
Index Terms
- CEGF: corner extraction by GPS filtering for power-efficient location uploading
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