sean j. barbeau, philip l. winters, rafael a. perez, miguel a. labrador, nevine l. georggi
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
U.S. Patent #8,036,679 – Optimizing Performance of Location-Aware Applications Using State [email protected]
(813) 974-7208locationaware.usf.edu
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
GPS Auto-SleepOptimizing performance of location-aware mobile apps
GPS-enabled mobile phones provide many new opportunities for high-resolution Location-based Services (LBS) via mobile apps
a) Old low-res tracking b) New high-res tracking
Problem
Frequent use of GPS severely affects battery life of mobile devices
Sprint CDMA EV-DO Rev. A
network
Sprint CDMA EV-DO Rev. A
network
4 sec. sampling interval0
1
2
3
4
5
6
7
8
9Negative Impact of GPS on Battery Life
Sanyo Pro 200
HTC Hero (Android 2.1)Ba
tter
y Li
fe (h
ours
)
29.7 meters
4 second GPS sampling
5 minute GPS sampling
Challenge
Moving
Stoppe
d
Prototype Testing with Mobile Devices Conclusion
Acknowledgements4 8 15 30 60 150 30005
1015202530354045
Interval Between GPS Fixes (s)
Batt
ery
Life
(hou
rs)
Varying GPS Interval Saves En-ergy
Sprint-Nextel for providing mobile devices and cellular service for this research
0
50
100
150
200
250
300
Inte
rval
Bet
wee
n G
PS F
ixes
(s
econ
ds)
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?
State0
State1
Staten – 1
Staten
Move directly to state[0] when speed exceeds high_speed threshold
Location Recalculation
Interval = 4 sec.
Location Recalculation
Interval = 8 sec.
Location Recalculation
Interval = 64 sec.
Location Recalculation
Interval = 128 sec.
Move gradually towards state[n] when (speed < low_speed value) and (distance_between_fixes < distance_threshold).
Move gradually towards state[0] when (speed < high_speed value) and (distance_between_fixes > distance_threshold).
Innovation
We implement this concept as a state machine in mobile app code. Will this limit the impact of GPS outliers on GPS sampling interval changes and increase battery life?
“Awake” to “Asleep” Transitions
“Asleep”
“Awake”
Min Max Mean 95th30.00%40.00%50.00%60.00%70.00%80.00%90.00%
100.00%State Accuracy
GPS Auto-Sleep correctly tracks states (mean accuracy of 88.4%), and extends mobile device battery life from 8 to 16 or more hours.
Energy Benefits