Improving energy efficiency of location sensing on smartphones

By Zhenyun Zhuang, Kyu-Han Kim, J. Singh. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2010

398 citations recorded by the source corpus.

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SensLoc: sensing everyday places and paths using less energy (2010, methodology): “also uses an accelerometer to detect movements, schedules two different localization techniques, and adjusts sampling rates based on the battery-level [34].”
The Internet of Things: A Survey from the Data-Centric Perspective (2013, neutral): “Examples of specific methods include energy-timeliness tradeoffs [91], adaptive sampling [84], and application-specific collection modes [117].”
A Survey of Green Mobile Networks: Opportunities and Challenges (2011, background): “In order to improve the energy efficiency of current localization schemes, the substitution, suppression, piggybacking, and adaptation of localization sensing requests to conserve energy are more promising and practical as discussed in [122].”
Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons (2016, background): “For outdoor location-based service, it is well-known that the intensive use of GPS often leads to high energy consumption [170], which can cause complete drain of battery in short time.”
Energy-efficient rate-adaptive GPS-based positioning for smartphones (2010, background): “[29] have proposed a location-sensing framework that includes four design principles – accelerometerbased suppression, location-sensing piggybacking, substitution of location-sensing mechanisms, and adaptation of sensing parameters when battery is low – to improve the energy efficiency of localizati”