Conference Proceedings
Energy adaptive sensor scheduling for noisy sensor measurements
S Maheswararajah, SM Guru, Y Shu, S Halgamuge
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics | SPRINGER-VERLAG BERLIN | Published : 2009
Abstract
In wireless sensor network applications, sensor measurements are corrupted by noises resulting from harsh environmental conditions, hardware and transmission errors. Minimising the impact of noise in an energy constrained sensor network is a challenging task. We study the problem of estimating environmental phenomena (e.g., temperature, humidity, pressure) based on noisy sensor measurements to minimise the estimation error. An environmental phenomenon is modeled using linear Gaussian dynamics and the Kalman filtering technique is used for the estimation. At each time step, a group of sensors is scheduled to transmit data to the base station to minimise the total estimated error for a given e..
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Funding Acknowledgements
This work was conducted when Suhinthan was an intern student at the CSIRO Tasmanian ICT Centre. The authors would like to thank Stephen Guigni, Greg Timms and Paulo De Souza for providing comments on the manuscript. The CSIRO Tasmanian ICT Centre is jointly funded by the Australian Government through the Intelligent Island Program and Australias Commonwealth Scientific and Industrial Research Organisation (CSIRO). The Intelligent Island Program is administered by the Tasmanian Department of Economic Development and Tourism.