Adaptive Sensing Based on Profiles for Sensor Systems

This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

[1]  Eric Horvitz,et al.  Layered representations for learning and inferring office activity from multiple sensory channels , 2004, Comput. Vis. Image Underst..

[2]  Kenneth Meijer,et al.  Activity identification using body-mounted sensors—a review of classification techniques , 2009, Physiological measurement.

[3]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[4]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[5]  Qiang Yang,et al.  Sensor-Based Abnormal Human-Activity Detection , 2008, IEEE Transactions on Knowledge and Data Engineering.

[6]  Gaurav S. Sukhatme,et al.  Connecting the Physical World with Pervasive Networks , 2002, IEEE Pervasive Comput..

[7]  Mark G. Terwilliger,et al.  Overview of Sensor Networks , 2004 .

[8]  Hans Mulder,et al.  Smart sensors to network the world. , 2004, Scientific American.

[9]  Yoshiteru Ishida.  Designing an Immunity-Based Sensor Network for Sensor-Based Diagnosis of Automobile Engines , 2006, KES.

[10]  石田 好輝.  Immunity-based systems : a design perspective , 2004 .

[11]  Christopher G. Atkeson,et al.  Simultaneous Tracking and Activity Recognition (STAR) Using Many Anonymous, Binary Sensors , 2005, Pervasive.

[12]  Aaron F. Bobick,et al.  Parametric Hidden Markov Models for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Mani Srivastava,et al.  Overview of sensor networks , 2004 .

[14]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.