With demographic changes of the aging population and the increasing number of people living alone, pervasive home monitoring is set to play an important role in maintaining the independence and improving the quality of life for the elderly. The UbiSense† project aims to establish smart sensing networks based on low cost embedded video platforms for movement tracking and gait, posture analysis. ...

In this paper, we seek answer to the question: can a wireless sensing system with energy harvesting power supplies perform as well as the one with conventional power supplies? Conventional sensing systems with deterministic energy sources usually employ uniform sampling. However, due to the stochastic nature of the energy harvested from the ambient environment, uniform sampling is usually infea...

A high-resolution fiber Bragg grating (FBG) sensor system using a linear-cavity fiber laser scheme is proposed and numerically studied. The proposed sensor system can improve the sensing accuracy by using a discriminating FBG pair in conjunction with a fiber laser scheme. This FBG sensor system can resolve the temperature up to 0.0005°C theoretically and can be applied for strain sensing and te...

Cognitive radio arises as a hot research issue in wireless communications recently, attributed to its capability of enhancing spectral efficiency and catering for the growing demand for bandwidth. As a good embodiment of cognitive radio’s unique feature, i.e. making use of every bit spectral resource, spectrum sensing plays a vital role in the implementation of cognitive radio. To alleviate neg...

In this paper, we investigate the energy efficiency and throughput optimization problem of cognitive relay networks. We propose to design sensing time and signal to noise ratio (SNR) to maximize the energy efficiency and throughput, since analytical and empirical studies have shown that sensing time and SNR are key factors for energy efficiency and throughput. We design a method that simultaneo...

SUMMARY Due to the influence of variations in landform, geophysical data acquisition is usually sub-sampled. Reconstruction of the seismic wavefield from sub-sampled data is an ill-posed inverse problem. Compressive sensing can be used to recover the original geophysical data from the sub-sampled data. In this paper, we consider the wavefield reconstruction problem as a com-pressive sensing and...