BeepBeep: a high accuracy acoustic ranging system using COTS mobile devices
Proceedings of the 5th international conference on Embedded networked sensor systems
Micro-Blog: sharing and querying content through mobile phones and social participation
Proceedings of the 6th international conference on Mobile systems, applications, and services
EnTracked: energy-efficient robust position tracking for mobile devices
Proceedings of the 7th international conference on Mobile systems, applications, and services
SurroundSense: mobile phone localization via ambience fingerprinting
Proceedings of the 15th annual international conference on Mobile computing and networking
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Energy-accuracy trade-off for continuous mobile device location
Proceedings of the 8th international conference on Mobile systems, applications, and services
Energy-efficient rate-adaptive GPS-based positioning for smartphones
Proceedings of the 8th international conference on Mobile systems, applications, and services
Activity recognition using cell phone accelerometers
ACM SIGKDD Explorations Newsletter
A practical approach to recognizing physical activities
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
ACM SIGSPATIAL GIS Cup 2013: geo-fencing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Location-based services (LBSs) are often based on an area or place as opposed to an accurate determination of the precise location. However, current mobile software frameworks are geared towards using specific hardware devices (e.g., GPS or 3G or WiFi interfaces) for as precise localization as possible using that device, often at the cost of a significant energy drain. Further, often the location information is not returned promptly enough. To address this problem, we design a framework for mobile devices, called Geo-fencing. The proposed framework is based on the observation that users move from one place to another and then stay at that place for a while. These places can be, for example, airports, shopping centers, home, offices and so on. Geo-fencing defines such places as geographic areas bounded by polygons. It assumes people simply move from fence to fence and stay inside fences for a while. The framework is coordinated with available communication chips and sensors based on their energy usage and accuracy provided. The essential goal is to determine when users check in or out of fences in an energy effiecient fashion so that appropriate LBS can be triggered. Windows based smartphones are used to prototype Geo-fencing. Validations are conducted with the resulting traces of outdoor and indoor activities of several users for several months. The results show that Geo-fencing provides an effective framework for use with LBSs with a significant energy saving for mobile devices.