2017 ◽  
Vol 115 ◽  
pp. 100-109 ◽  
Author(s):  
Jing Wang ◽  
Jian Tang ◽  
Guoliang Xue ◽  
Dejun Yang

Author(s):  
Ryo Takahashi ◽  
Wakako Yukita ◽  
Takuya Sasatani ◽  
Tomoyuki Yokota ◽  
Takao Someya ◽  
...  

Energy-efficient and unconstrained wearable sensing platforms are essential for ubiquitous healthcare and activity monitoring applications. This paper presents Twin Meander Coil for wirelessly connecting battery-free on-body sensors to a textile-based reader knitted into clothing. This connection is based on passive inductive telemetry (PIT), wherein an external reader coil collects data from passive sensor coils via the magnetic field. In contrast to standard active sensing techniques, PIT does not require the reader to power up the sensors. Thus, the reader can be fabricated using a lossy conductive thread and industrial knitting machines. Furthermore, the sensors can superimpose information such as ID, touch, rotation, and pressure on its frequency response. However, conventional PIT technology needs a strong coupling between the reader and the sensor, requiring the reader to be small to the same extent as the sensors' size. Thus, applying this technology to body-scale sensing systems is challenging. To enable body-scale readout, Twin Meander Coil enhances the sensitivity of PIT technology by dividing the body-scale meander-shaped reader coils into two parts and integrating them so that they support the readout of each other. To demonstrate its feasibility, we built a prototype with a knitting machine, evaluated its sensing ability, and demonstrated several applications.


2016 ◽  
Vol 34 (12) ◽  
pp. 4048-4062 ◽  
Author(s):  
Weiwei Wu ◽  
Jianping Wang ◽  
Minming Li ◽  
Kai Liu ◽  
Feng Shan ◽  
...  

Author(s):  
Martin Peckerar ◽  
Anastasios Tousimis

Solid state x-ray sensing systems have been used for many years in conjunction with scanning and transmission electron microscopes. Such systems conveniently provide users with elemental area maps and quantitative chemical analyses of samples. Improvements on these tools are currently sought in the following areas: sensitivity at longer and shorter x-ray wavelengths and minimization of noise-broadening of spectral lines. In this paper, we review basic limitations and recent advances in each of these areas. Throughout the review, we emphasize the systems nature of the problem. That is. limitations exist not only in the sensor elements but also in the preamplifier/amplifier chain and in the interfaces between these components.Solid state x-ray sensors usually function by way of incident photons creating electron-hole pairs in semiconductor material. This radiation-produced mobile charge is swept into external circuitry by electric fields in the semiconductor bulk.


2011 ◽  
Author(s):  
B. Smitha Shekar ◽  
M. Sudhakar Pillai ◽  
G. Narendra Kumar

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.


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