Juan Ye, Simon Dobson, Susan McKeever

Pervasive systems must offer an open, extensible, and evolving portfolio of services which integrate sensor data from a diverse range of sources. The core challenge is to provide appropriate and consistent adaptive behaviours for these services in the face of huge volumes of sensor data exhibiting varying degrees of precision, accuracy and dynamism. Situation identification is an enabling technology that resolves noisy sensor data and abstracts it into higher-level concepts that are interesting to applications. We provide a comprehensive analysis of the nature and characteristics of situations, discuss the complexities of situation identification, and review the techniques that are most popularly used in modelling and inferring situations from sensor data. We compare and contrast these techniques, and conclude by identifying some of the open research opportunities in the area.

Pervasive and Mobile Computing 8(1), pages 36-66, February 2012
Author = {Ye, Juan and Dobson, Simon and McKeever, Susan},
Doi = {10.1016/j.pmcj.2011.01.004},
Issn = {1574-1192},
Journal = {Pervasive and Mobile Computing},
Month = feb,
Number = 1,
Pages = {36--66},
Title = {Situation Identification Techniques in Pervasive Computing: A Review},
Url = {http://www.sciencedirect.com/science/article/pii/S1574119211000253},
Volume = 8,
Year = 2012}


Publication Data

2011 © aliCE Research Group @ DEIS, Alma Mater Studiorum-Università di Bologna