Energy-efficient WiFi scanning for localization

WiFi radio signals are commonly used for the localization of mobile devices. However, frequent scanning of WiFi reduces user experiences because it consumes significant energy on mobile devices. In this paper, we propose an energy-efficient WiFi scan system for localization. The proposed system preserves the quality of service of each application and minimizes the energy consumption of WiFi scanning. The main idea is that the system adaptively controls the dwell time of beacon-listening in given locations. We predict the number of scanned access points (APs) according to locations and optimize the dwell time of beacon-listening to obtain the minimum number of scanned APs. The evaluation shows that the proposed system saves the energy consumption of WiFi scans by 33.6% and 45.7%, according to the number of scanned APs, while not decreasing the accuracy of localization in indoor and outdoor scenarios.     

A computationally efficient approach for hidden-Markov model-augmented fingerprint-based positioning

This paper presents a computationally efficient approach for mobile subscriber position estimation in wireless networks. A method of data scaling assisted by timing adjust is introduced in fingerprint-based location estimation under a framework which allows for minimising computational cost. The proposed method maintains a comparable level of accuracy to the traditional case where no data scaling is used and is evaluated in a simulated environment under varying channel conditions. The proposed scheme is studied when it is augmented by a hidden-Markov model to match the internal parameters to the channel conditions that present, thus minimising computational cost while maximising accuracy. Furthermore, the timing adjust quantity, available in modern wireless signalling messages, is shown to be able to further reduce computational cost and increase accuracy when available. The results may be seen as a significant step towards integrating advanced position-based modelling with power-sensitive mobile devices.     

Wi-Fi fingerprinting based on collaborative confidence level training

Wi-Fi fingerprinting has been a popular indoor positioning technique with the advantage that infrastructures are readily available in most urban areas. However wireless signals are prone to fluctuation and noise, introducing errors in the final positioning result. This paper proposes a new fingerprint training method where a number of users train collaboratively and a confidence factor is generated for each fingerprint. Fingerprinting is carried out where potential fingerprints are extracted based on the confidence factor. Positioning accuracy improves by 40% when the new fingerprinting method is implemented and maximum error is reduced by 35%.     

基于物联网的矿井通风机监控系统研究

针对当前矿井通风机监控系统功能单一、反馈控制能力差能等特点,提出一种基于物联网的矿井通风机监控系统。该系统利用传感器、Wi Fi技术实现监控系统实时数据传输和反馈报警控制功能。详细描述了矿井通风机监控系统构成及各硬件设计原理图,介绍了系统的底层驱动设计及软件设计流程。通过实验证明该矿井通风机监控系统能实时传输数据,视频监控稳定,能实现报警控制,可在移动平台或者PC机上进行监控,具有一定的推广价值。     

基于WiFi构建的智能家居控制系统的设计

介绍了一种新型的基于WiFi构建的智能家居控制系统,系统采用PC主机和智能手机作为基本硬件平台,辅助WiFi智能插座,WiFi智能传感器,就可以实现智能家居控制系统。利用PC机做智能家居控制系统的中央处理器,手持终端设备(通常是智能手机)作控制媒介,实现对智能家居的控制。在系统的软件部分,PC机采用Linux或windows操作系统,使用JavaScript作为网络服务器脚本语言编写;智能手机采用通用的Android系统,采用java语言编写;它们及控制接口的Web通信采用Node.js技术实现。通过对系统进行性能测试,结果表明,系统运行稳定,实时性好,性价比高,具有一定的实用价值。     

基于FH-AC系统Portal认证的实现与开发

随着当今移动互联网的快速发展,Wi Fi设备成为人们生活当中不可缺少的组成部分,而传统的无线网络在接入稳定性和安全性方面有待进一步提高。为了解决上述问题,设计了基于FH-AC系统的Portal认证系统。该系统通过对原有Portal协议进行改进并且采用Socket/HTTP通信和CHAP认证技术等一系列技术来提升系统性能,使整个系统在使用过程中能够更快更稳定地接入当前无线网络,其系统安全性也得到进一步的提升。     

Theoretical performance analysis of radio frequency fingerprinting under receiver distortions

Radio frequency fingerprinting (RFF) is used to uniquely identify individual emitters by exploiting the radio frequency characteristics, which are originated from transmitter imperfections. The theoretical performance is analyzed to evaluate the feasibility of RFF with channel noise and receiver imperfections. The distortions from oscillators and analog‐to‐digital converter (ADC) are considered, and a RFF signal model describing the discrepancies of transmitter imperfections, channel noise, and receiver distortions are constructed. A likelihood ratio test algorithm for RFF is proposed to analyze the theoretical performance. The upper and lower bound of theoretic performance is derived through the analysis of the likelihood ratio test statistic, which enlightens how to design a “just enough” receiver to meet the demands of RFF. The simulation results are in agreement with the theoretical evaluation. Copyright © 2013 John Wiley & Sons, Ltd.     

煤矿搜救蛇形机器人MK-01控制系统设计

为用于煤矿搜救的蛇形机器人MK-01设计了一个控制系统。该系统能够利用机器人自身携带的仪器设备采集煤矿巷道内部的状态信息,通过无线网络将信息传输给地面系统,为营救人员施救提供依据。该系统对提高煤矿搜救的智能化、自动化水平,降低搜救成本、提高搜救效率具有一定的意义。     

基于多元分类判别方法对普洱生茶进行产地溯源研究

目的 探究多元分类判别方法对普洱茶产地溯源的有效性与可行性。方法 基于云南5个产地的60份普洱茶生茶样本,利用5种有机成分以及36种矿物元素的含量,结合主成分分析、判别分析和多层感知器分析等多元分类方法构建普洱茶产地溯源模型。结果 普洱茶(生茶)中总计33项指标具有与产地的显著相关性。不同产地的普洱茶样本在主成分上有差异,但分类的准确性较低。通过判别分析得到了普洱茶产地溯源的判别函数和组质心函数,该样本溯源正确率高于98%。通过多层感知器分析,该方法的分类正确率最高,生茶样本的训练集和测试集分类正确率分别为100.0%和95.5%。结论 普洱茶中有机成分与矿物元素受环境因素影响,在各自产地间形成各自的指纹特征,多维组合可用于建立普洱茶产地溯源模型,为普洱茶产地追溯提供一定的方法支持。     

复方茵黄解毒汤乙酸乙酯有效部位薄层扫描指纹图谱的构建

初步构建复方茵黄解毒汤乙酸乙酯有效部位的指纹图谱,为复方茵黄解毒汤建立更高的质量标准打下基础.采用的方法是:以苯-乙酸乙酯-甲醇-甲酸(5∶1∶1.5∶5滴)为展开剂,用薄层色谱法对上述有效部位进行展开,运用岛津CS9000薄层扫描仪,选择λs=275 nm,λR=365 nm双波长扫描与λ=435 nm单波长扫描.结果表明:该部位薄层色谱峰得到较好分离,获得了较理想的薄层色谱指纹图谱,并确定其中小檗碱、咖啡酸、阿魏酸和大黄酸峰的归属.该方法简便、快速、精密度较高、重现性较好,可用于该复方中药制剂的质量控制.