creators_name: Osborne, Michael A
creators_name: Roberts, Stephen J
creators_name: Rogers, Alex
creators_name: Jennings, Nicholas R
type: article
datestamp: 2011-11-14 09:54:50
lastmod: 2012-03-22 09:40:51
metadata_visibility: show
title: Real-Time Information Processing of
Environmental Sensor Network Data
ispublished: inpress
subjects: ABC
subjects: app
subjects: ie
full_text_status: public
abstract: In this paper, we consider the problem faced by a sensor network operator who must infer, in
real-time, the value of some environmental parameter that is being monitored at discrete points
in space and time by a sensor network. We describe a powerful and generic approach built
upon an efficient multi-output Gaussian process that facilitates this information acquisition and
processing. Our algorithm allows effective inference even with minimal domain knowledge, and we
further introduce a formulation of Bayesian Monte Carlo to permit the principled management of
the hyperparameters introduced by our flexible models. We demonstrate how our methods can be
applied in cases where the data is delayed, intermittently missing, censored and/or correlated. We
validate our approach using data collected from three networks of weather sensors and show that
it yields better inference performance than both conventional independent Gaussian processes and
the Kalman filter. Finally, we show that our formalism efficiently re-uses previous computations
by following an online update procedure as new data sequentially arrives, and that this results in
a four-fold increase in computational speed in the largest cases considered.
date: 2012
date_type: submitted
publication: ACM Transactions on Sensor Networks
volume: 9
number: 1
refereed: TRUE
citation:   Osborne, Michael A and Roberts, Stephen J and Rogers, Alex and Jennings, Nicholas R  (2012) Real-Time Information Processing of Environmental Sensor Network Data.  ACM Transactions on Sensor Networks, 9 (1).      (In Press)  
document_url: http://www.orchid.ac.uk/eprints/11/1/tosn_gp_revised.pdf