MobiCon: a mobile context-monitoring platform

User context is defined by data generated through everyday physical activity in sensor-rich, resource-limited mobile environments.

[1]  Inseok Hwang,et al.  E-Gesture: a collaborative architecture for energy-efficient gesture recognition with hand-worn sensor and mobile devices , 2011, SenSys.

[2]  Mahadev Satyanarayanan,et al.  Agile application-aware adaptation for mobility , 1997, SOSP.

[3]  S. Sitharama Iyengar,et al.  Fundamentals of Sensor Network Programming: Applications and Technology , 2010 .

[4]  Lama Nachman,et al.  Don't slow me down: Bringing energy efficiency to continuous gesture recognition , 2010, International Symposium on Wearable Computers (ISWC) 2010.

[5]  Youngki Lee,et al.  SeeMon: scalable and energy-efficient context monitoring framework for sensor-rich mobile environments , 2008, MobiSys '08.

[6]  Mark D. Corner,et al.  Eon: a language and runtime system for perpetual systems , 2007, SenSys '07.

[7]  Amin Vahdat,et al.  ECOSystem: managing energy as a first class operating system resource , 2002, ASPLOS X.

[8]  Youngki Lee,et al.  Orchestrator: An active resource orchestration framework for mobile context monitoring in sensor-rich mobile environments , 2010, 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[9]  Gerhard Tröster,et al.  SwimMaster: a wearable assistant for swimmer , 2009, UbiComp.

[10]  Mark D. Corner,et al.  Turducken: hierarchical power management for mobile devices , 2005, MobiSys '05.

[11]  Margaret Martonosi,et al.  Data compression algorithms for energy-constrained devices in delay tolerant networks , 2006, SenSys '06.

[12]  Sang Jeong Lee,et al.  BMQ-Processor: A High-Performance Border-Crossing Event Detection Framework for Large-Scale Monitoring Applications , 2009, IEEE Transactions on Knowledge and Data Engineering.

[13]  Gregory Vert,et al.  Introduction to Contextual Processing: Theory and Applications , 2010 .

[14]  Yi Wang,et al.  A framework of energy efficient mobile sensing for automatic user state recognition , 2009, MobiSys '09.

[15]  Matt Welsh,et al.  Resource aware programming in the Pixie OS , 2008, SenSys '08.

[16]  Prashant J. Shenoy,et al.  Chameleon: Application-Level Power Management , 2008, IEEE Transactions on Mobile Computing.

[17]  Shyamal Patel,et al.  Mercury: a wearable sensor network platform for high-fidelity motion analysis , 2009, SenSys '09.

[18]  Siobhán Clarke,et al.  CASS - Middleware for Mobile Context-Aware Applications , 1990 .

[19]  Taiwoo Park,et al.  Swan boat: pervasive social game to enhance treadmill running , 2009, ACM Multimedia.

[20]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[21]  Pedro José Marrón,et al.  Meeting lifetime goals with energy levels , 2007, SenSys '07.

[22]  Gang Zhou,et al.  Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information , 2009, 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks.

[23]  Mathias Stäger,et al.  Empirical Study of Design Choices in Multi-Sensor Context Recognition Systems , 2005 .

[24]  Oriana Riva,et al.  Contory: A Middleware for the Provisioning of Context Information on Smart Phones , 2006, Middleware.

[25]  Taiwoo Park,et al.  Transforming solitary exercises into social exergames , 2012, CSCW.