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On The Problem of Energy Efficient Mechanisms Based on Data Reduction in Wireless Body Sensor Networks

Authors:
Carol Habib
Abdallah Makhoul
Raphael Couturier
Rony Darazi

Keywords: Body Sensor Networks, Energy Consumption, Compressive Sensing, Adaptive Sampling

Abstract:
Wireless Body Sensor Networks have emerged as a low-cost solution for healthcare applications and telemedicine solutions replacing unnecessary hospitalization and ensuring continous health monitoring. Many challenges exist in such a network, especially because the sensor nodes have limited resources. In this paper, the energy consumption problem due to periodic transmission is targeted. We present a work in progress on energy-efficient mechanisms based on data reduction for body sensor networks. Many approaches have been proposed in the literature that aim to reduce the size and the amount of data collected and sent via the network. Our main idea in this paper is to confront Compressive Sensing (CS) and adaptive sampling techniques in order to come out with a problem formulation and a comprehensive comparison. The objective is to show if the adaptive sampling approach which is based on on-node processing ensure a better Performance/Energy trade-off than CS theory applied on biosignals.

Pages: 94 to 98

Copyright: Copyright (c) IARIA, 2017

Publication date: September 10, 2017

Published in: conference

ISSN: 2308-4405

ISBN: 978-1-61208-580-7

Location: Rome, Italy

Dates: from September 10, 2017 to September 14, 2017