Fault tolerant multiple event detection in a wireless sensor network

With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P$P$) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P$P$ can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10%$10\%$ with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94%$94\%$ and it increases with increase in node density.     

Remote flood monitoring system based on plastic optical fibres and wireless motes

This paper summarises an effort in the development of a remote flood monitoring system based on plastic optical fibre (POF) sensors and a wireless mote network. The wireless mote, comprising of a network of MICA2DOT™ units, was used as a platform to monitor and record the signal from the POF sensors and transmit this information to a base station wirelessly. A prototype of the integrated wireless POF sensor unit has been constructed, rendering it possible to deploy the autonomous unit remotely at multiple monitoring points as required. A flood monitoring simulation was carried out in a 24 m × 10 m × 0.9 m wave basin where four of these wireless optical fibre mote sensors were used to detect the rising water level in the basin. The novelty of the work lies in the successful integration of the wireless platform to a POF-based liquid level sensor and the subsequent demonstration of the prototype of the system for the purposes of flood monitoring applications.The sensing principle of the POF sensor developed here is well-known and is based on the loss of total internal reflection of the optical signal as the sensor probe comes in contact with the liquid. Compared to optical fibre-based sensors reported previously in the literature, the probe profile used in this study differs in terms of its simplicity in design, while exhibiting an excellent signal intensity loss ratio without the need for additional attachments to the probe such as optical prisms. The tests carried out showed that the POF sensor is capable of detecting a variety of fluids. Exhibiting good signal stability, the sensor also detects the liquid level reliably when the liquid rises or falls to the predetermined level. The responsiveness of the optical fibre sensor was evaluated by simulating different rates at which the liquid rises by immersing the sensor tip into the liquid and vice-versa at various speeds ranging from 1 mm/min to 500 mm/min.     

基于MC9S12NE64的以太网测控系统的设计

嵌入式测控系统是当前工业自动化测控应用领域研究的热点之一。本文利用Freescale公司的MC9S12NE64MCU,运用其内部10位A/D模块,进行数据采集,并通过其集成的以太网网络模块实现了数据上传和远程控制。     

基于Internet的电梯ARS监控系统的设计与实现

电梯ARS（自动逃生）系统是在电梯供电中断等紧急情况下,帮助乘客逃生的自动化系统。在整个监控系统中,包括本地和远程监控两部分。该文介绍了监控系统的功能,设计与实现。本地监控通过串口通信与下位机进行通信来实现数据的采集,远程的实现是应用微软公司开发的语言C#,以网络编程核心Windows Sockets和客户／服务器模式为基础,运用ADO．NET类融合数据库Access和．NET Remoting网络技术,完成一个远程分布式数据库查询系统,以实现电梯ARS远程监控功能。     

基于Web的达梦数据库交互式查询工具的实现

本系统主要功能：对用户输入的单句或多句SQL语句进行处理,及时返回查询结果或者操作信息。本系统具有以下特点：采用主流的Web设计语言JSP设计客户端界面,用JDBC实现对数据库的无缝连接;使用JDBC扩展包中的行集来缓存结果集;使用javacc工具自动生成语法分析器;这些后台操作大部分采用了JavaBeans进行封装。     

微机联锁远程故障诊断系统的研究

作者论述了微机联锁远程故障诊断系统的构成和实现,提出现阶段信号维修改革的任务、组织管理及实施远程故障诊断系统的关键技术。     

伪不变特征法在遥感影像归一化处理中的应用

提出了一套伪不变特征法（PIF）归一化处理多时相遥感影像的技术流程和方法: 即参考影像选择,参考影像大气辐射校正,伪不变特征点选取,回归模型建立及结果评价,并对处理流程中的各个环节加以详细说明。其中在样本点选取过程中尝试把人工直接选取伪不变特征点应用于实践,并用主成分分析法对处理结果进行评价,评价结果表明人工直接选取伪不变特征点,对多时相遥感影像进行归一化处理是可行的,达到了消除季节性地物辐射变化、太阳光照条件差异、气象条件（大气散射、吸收和云量变化等）波动大等因素的影响,处理后的影像能满足建立模型的要求。

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面向对象的海岸带养殖水域提取

在海岸带遥感地物自动信息提取工作中,传统基于像元的图像处理技术难以解决由于地物混杂带来的椒盐噪声现象。提出了一种面向对象的养殖水域提取方法,该方法分为4步：① 结合eCognition分割算法的基本思想,设计并使用了多精度图像分割算法获得分割图斑;② 计算图斑的多类特征,包括光谱、形状、纹理、空间关系等,为后续分析服务;③ 通过基于图斑的多特征分析,提取出水域全图以及其派生的面状水域、线状水域;④ 在所有水域中剔除面状水域和线状水域,获得养殖水域。在SPOT\|5高分辨率遥感影像上的提取实验证明该方法是可行的。     

南海北部油气分布的遥感探测方法研究

随着卫星和传感器技术的发展,遥感技术已广泛应用于油气资源调查与勘探,且发挥着越来越重要的作用。通过阐述油气烃类微渗漏模型,认为油气烃类微渗漏可以导致海表烃类气体、油膜异常及喜烃类生物聚集。并以南海北部边缘盆地为例,阐明了海洋油气遥感探测的3种方法：①利用红外波段反演海表温度异常。②利用合成孔径雷达检测海表油膜异常。③喜烃类生物的增加导致海表光谱异常,以及利用水色遥感技术检测海表微生物含量异常。最后,对海洋油气遥感的未来发展趋势进行了展望。     

基于H．323协议和帧中继网络的远程监控系统实现

目前H.323协议已成为视频技术的发展重点,帧中继接入方式具有多方面的优势.提出一种基于H.323协议族的H.263和G.729协议标准和帧中继接入方式的远程监控系统的实现方案,分析系统组成结构,并探讨了相关的关键技术.