Multi-sensor fusion based intelligent sensor relocation for health and safety monitoring in BSNs

Abstract

The body sensor networks (BSNs) have attracted great attention due to their numerous important features and wide applications in health and safety monitoring, especially in some hostile or potentially dangerous workplaces. In this paper, aiming to provide continuous coverage from the initial Region of Interest (ROI) to a New Region of Interest (NROI) to trace the BSNs for human health and safety monitoring, we formulate and define the novel confident information coverage (CIC)-based Intelligent Sensor Relocation for NROI (CIC-ISR-NROI) problem in mobile wireless sensor networks (MWSNs) based on the novel CIC model. For handing the CIC-ISR-NROI problem, we develop two energy-efficient intelligent sensor relocation algorithms based on multi-sensor fusion, the Rapid Relocation Time Low Energy Consumption (RRTLEC) algorithm and optimized RRTLEC algorithm, to relocate redundant mobile sensors from the ROI to cover the NROI in a timely and energy-efficient manner while constructing the communication chain to connect the ROI and the NROI. To verify the effectiveness and efficiency of the proposed schemes, we conduct a series of experiments which correspond to the realistic scenarios in health and safety monitoring in the 272 uranium tailing. Experimental results show that the performance of our approaches is better than the other typical peer approaches by the metrics of the total moving energy consumption and the maximum relocation time.