Research Article
Prediction-based data transmission for energy conservation in wireless body sensors
@INPROCEEDINGS{10.4108/ICST.WICON2010.8543, author={Feng Xia and Zhenzhen Xu and Lin Yao and Weifeng Sun and Mingchu Li}, title={Prediction-based data transmission for energy conservation in wireless body sensors}, proceedings={International Workshop on Ubiquitous Body Sensor Networks}, publisher={IEEE}, proceedings_a={UBSN}, year={2010}, month={4}, keywords={Body sensor networks Data communication Energy conservation Humans Medical services Monitoring Prediction algorithms Sensor phenomena and characterization Wearable sensors Wireless sensor networks}, doi={10.4108/ICST.WICON2010.8543} }- Feng Xia
Zhenzhen Xu
Lin Yao
Weifeng Sun
Mingchu Li
Year: 2010
Prediction-based data transmission for energy conservation in wireless body sensors
UBSN
IEEE
DOI: 10.4108/ICST.WICON2010.8543
Abstract
Wireless body sensors are becoming popular in healthcare applications. Since they are either worn or implanted into human body, these sensors must be very small in size and light in weight. The energy consequently becomes an extremely scarce resource, and energy conservation turns into a first class design issue for body sensor networks (BSNs). This paper deals with this issue by taking into account the unique characteristics of BSNs in contrast to conventional wireless sensor networks (WSNs) for e.g. environment monitoring. A prediction-based data transmission approach suitable for BSNs is presented, which combines a dual prediction framework and a low-complexity prediction algorithm that takes advantage of PIF (proportional-integral-derivative) control. Both the framework and the algorithm are generic, making the proposed approach widely applicable. The effectiveness of the approach is verified through simulations using real-world health monitoring datasets.