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GPS Auto-Sleep Optimizing performance of location-aware mobile apps. Sean J. Barbeau, Philip L. Winters, Rafael A. Perez, Miguel A. Labrador, Nevine L. Georggi. Center for Urban Transportation Research and Department of Computer Science & Engineering. Introduction. Problem. Sprint CDMA
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GPS Auto-Sleep Optimizing performance of location-aware mobile apps Sean J. Barbeau, Philip L. Winters, Rafael A. Perez, Miguel A. Labrador, Nevine L. Georggi Center for Urban Transportation Research and Department of Computer Science & Engineering Introduction Problem Sprint CDMA EV-DO Rev. A network Sprint CDMA EV-DO Rev. A network a) Old low-res tracking b) New high-res tracking GPS-enabled mobile phones provide many new opportunities for high-resolution Location-based Services (LBS) via mobile apps Frequent use of GPS severely affects battery life of mobile devices Challenge Innovation What if we could dynamically change the GPS sampling interval on the phone? Would this save battery life while providing high-res tracking? Problem: GPS error makes detecting stops and starts difficult. Error frequently triggers false GPS on/offs What if we treat the problem as continuum instead of binary state? We implement this concept as a state machine in mobile app code. Will this limit the impact of GPS outliers on GPS samplinginterval changes and increase battery life? 4 second GPS sampling 5 minute GPS sampling 29.7 meters Prototype Testing with Mobile Devices Conclusion “Awake” to “Asleep” Transitions State Accuracy Energy Benefits “Asleep” GPS Auto-Sleep correctly tracks states (mean accuracy of 88.4%), and extends mobile device battery life from 8 to 16 or more hours. Acknowledgements “Awake” Sprint-Nextel for providing mobile devices and cellular service for this research U.S. Patent #8,036,679 – Optimizing Performance of Location-Aware Applications Using State Machines barbeau@cutr.usf.edu (813) 974-7208 locationaware.usf.edu