  Sensor Networks produce a large amount of data. According to the needs this
data requires to be processed, delivered and accessed. This processed data when
made available with the physical device location, user preferences, time
constraints; generically called as context-awareness; is widely referred to as
the core function for ubiquitous systems. To our best knowledge there is lack
of analysis of context information fusion for ubiquitous sensor networks.
Adopting appropriate information fusion techniques can help in screening noisy
measurements, control data in the network and take necessary inferences that
can help in contextual computing. In this paper we try and explore different
context information fusion techniques by comparing a large number of solutions,
their methods, architectures and models.
