基于无线射频和GPRS网络的林火监测数据采集电路设计

本监测系统利用无线射频与GPRS网络相结合的方式,监测终端将温度传感器与烟雾浓度传感器采集到的数据通过无线射频发送到基站,再通过基站的GPRS网络将数据发送到监控中心,来实现对林火的实时监测。通过监控中心对整个网络的控制,可以实时监测森林的状况。本监测系统结合无线射频和GPRS网络的优势,无线射频使监测终端更加方便安装,GPRS网络可以实现远程监控管理。本监测系统可以通过短信、服务器、定时和报警触发方式启动,可以实时采集现场数据。本设计的硬件电路以LPC767芯片为核心,采用RF200无线射频芯片和MC55模块进行了各种外围电路设计,采取了低功耗与抗干扰措施。制作出了电路板,并且完成了部分功能的测试。     

A Centralized Mechanism for Preventing DDOS Attack in Wireless Sensor Networks

Wireless sensor networks face numerous limitations. Security and Privacy are the two most essential parameters that require consideration in wireless sensor networks for conveying responsive information amid basic applications. High density and limited communication range of sensor nodes, forwarding packets in sensor networks have caused the performance of during multi-hop data transmission. Hence communication with different devices these days are not secure, due to the absence of centralized monitoring and overprotective requirements. This paper is related to speak about Distributed Denial of Service which debilitates the ability of the network and the data being transmitted. The earlier system guarantees the WSN through a self arranged and confined procedure between the nodes in the sensor environment. Here, the authors present the Centralized Detect Eliminate and Control algorithm for authorization and centralized monitoring component to discover the node that has turned into a victim node and to get rid of the information communicated to the fatality node from the neighbour nodes. Overprotective of the communication between the nodes leads to dependability. The simulation results improve the malicious node detection rate and increase the various parameters like throughput and reduce the average delay. This leads to, the overall detection rate built, eventually enhancing the parameters of the network environment.

     

Nature inspired discrete firefly algorithm for optimal mobile data gathering in wireless sensor networks

Nowadays wireless sensor networks enhance the life of human beings by helping them through several applications like precision agriculture, health monitoring, landslide detection, pollution control, etc. The built-in sensors on a sensor node are used to measure the various events like temperature, vibration, gas emission, etc., in the remotely deployed unmanned environment. The limited energy constraint of the sensor node causes a huge impact on the lifetime of the deployed network. The data transmitted by each sensor node cause significant energy consumption and it has to be efficiently used to improve the lifetime of the network. The energy consumption can be reduced significantly by incorporating mobility on a sink node. Thus the mobile data gathering can result in reduced energy consumption among all sensor nodes while transmitting their data. A special mobile sink node named as the mobile data transporter (MDT) is introduced in this paper to collect the information from the sensor nodes by visiting each of them and finally it sends them to the base station. The Data collection by the MDT is formulated as a discrete optimization problem which is termed as a data gathering tour problem. To reduce the distance traveled by the MDT during its tour, a nature-inspired heuristic discrete firefly algorithm is proposed in this paper to optimally collect the data from the sensor nodes. The proposed algorithm computes an optimal order to visit the sensor nodes by the MDT to collect their data with minimal travel distance. The proposed algorithm is compared with tree-based data collection approaches and ant colony optimization approach. The results demonstrate that the proposed algorithm outperform other approaches minimizing the tour length under different scenarios.     

Mobile Malicious Node Detection Using Mobile Agent in Cluster-Based Wireless Sensor Networks

Many application domains require that sensor node to be deployed in harsh or hostile environments, such as active volcano area tracking endangered species, etc. making these nodes more prone to failures. The most challenging problem is monitoring the illegal movement within the sensor networks. Attacker prefers mobile malicious node because by making the diversity of path intruder maximize his impact. The emerging technology of sensor network expected Intrusion detection technique for a dynamic environment. In this paper, a defective mechanism based on three-step negotiation is performed for identifying the mobile malicious node using the mobile agent. In many approaches, the multi-mobile agents are used to collect the data from all the sensor nodes after verification. But it is inefficient to verify all the sensor nodes (SNs) in the network, because of mobility, energy consumption, and high delay. In the proposed system this can be solved by grouping sensor nodes into clusters and a single mobile agent performs verification only with all the cluster heads instead of verifying all the SNs. The simulation result shows the proposed system shows a better result than the existing system.

     

基于ZigBee的风电机组振动故障监测系统设计

：针对目前风电机组有线监测系统安装、维护不便和监测点有限等问题,设计了基于ZigBee的风电机组振动故障监测系统,由传感器节点、协调器节点、3G网络和监控中心组成。传感器节点采集机组各部位的振动参数并发送至协调器节点,经过协调器节点处理的信息通过3G网络发送至远程监控中心,此设计提高了系统的可靠性和实时性。测试结果表明系统节点间通信良好,系统工作稳定性高,数据传输实时性好,及时给出报警信息,故障诊断正确率达到95.5%。     

Semisupervised Classification Based Clustering Approach in WSN for Forest Fire Detection

Forest fire is a very considerable problem of ecological system. This paper depicts a novel technique which detects the high active(HA) zone (nearer to the epicenter of fire) in the forest and transmits all sensed data to the base station through wireless communication as early as possible. Fire office takes necessary action to prevent the spreading of fire. For this purpose sensors are deployed in forest zone to sense different data which are necessary for detecting forest fire and divides it into different clusters. A semisupervised rule-based classification model is proposed in this paper to detect whether its zone is high active, medium active (MA) or low active (LA) cluster in the forest. We train our proposed integrated model in such a way when only one parameter of sensed data is transmitted by the sensor nodes due to energy constraint to the initiator of that zone, initiator can be able to predict the state of (HA,MA,LA) zone with 96% accuracy. All the sensor nodes in HA cluster transmit their packet through cluster head to the base station continuously applying greedy forwarding technique. Authors consider energy saving strategy during cluster head selection and data transmission in HA zone. On the other hand, sensors in MA zone transmit packet periodically and LA zone avoids to transmit the sensed data. This way proposed technique transmits the sensed data from HA zone efficiently and quickly to forest office for forest fire prevention and saves the energy of all sensor nodes in the forest.

     

无线传感器网络抗欺骗的节点定位算法

节点位置定位是无线传感器网络应用的基本要求之一。针对无线传感器网络在开放性环境中应用容易遭受恶意节点欺骗攻击的问题,设计了一种抗欺骗的节点安全定位算法。算法将参考节点进行分组划分,并通过不同分组之间定位结果的比较,排除其中可能存在的恶意节点。在分组过程中,算法同时考虑了参考节点的优选问题,避免不良拓扑结构造成的定位偏差。仿真试验分析表明,算法能够有效地抵抗恶意节点的定位信息欺骗,大大提高了网络节点的定位精度。     

基于信任机制的无线电环境地图重构

无线电环境地图系统中的感知节点被俘获后会受迫地向数据中心发送伪造数据,导致无线电环境地图精度降低.针对该问题,提出了基于信任机制的空间插值算法改进方案,并阐述了感知节点信任值更新策略.该方案通过改变感知节点的信任度来降低恶意节点的数据在空间插值算法中的权重,经过信任值的多次更新而最终隔离恶意节点.实验仿真中,均方根误差(RMSE)和误警区域率一正确检测区域率(FAZR-CDZR1)两种性能指标均表明所提方案能够有效遏制恶意节点的篡改数据攻击,保障了无线电环境地图的精确度.     

基于热红外光谱响应的油库火灾温度场反演方法研究

热辐射是油库火灾事故的主要危害特性之一,而温度场又是其直接表现形式,因此快速有效地监测温度场信息是迅速掌握灾情动态信息的最佳途径,对提高油库火灾事故应急监测与快速响应能力、维护人民生命财产安全、保护生态环境以及大幅减少经济损失等具有重要意义。在国内外地表温度反演方法研究进展的基础上,针对油库火灾爆炸事故的突发性特征,通过分析环境温度急剧变化、遥感影像及反演参数难以获取等因素,建立了一种基于热红外光谱和地面传感器数据的油库火灾温度场信息提取模型。通过设计模拟实验,成功反演了试验场及其周边区域的地表温度情况。结果表明,该模型能够快速有效地反演油库火灾事故发生区域的温度场信息。     

基于物联网云平台的中波发射台机房环境监测系统

利用物联网云平台技术搭建中波广播发射台机房环境监测系统,该系统实现气象条件、设备机房温湿度、发射机运行参数、门禁系统及供电系统的远程实时监控。物联网传感器完成设备房间环境数据的采集工作,通过边缘网关将数据发送到物联网云平台。客户端向云平台发送请求,订阅相关的信息和事件。该系统可以广泛应用于各种室内场景的环境监控,并根据实际情况进行二次开发。     

基于ZigBee和ARM技术的森林火情监测系统的设计

介绍了基一种基于ZigBee和ARM技术的无线森林火情监测系统。该系统采用无线传感网络结合上位机数据处理中心的框架,采取ZigBee和短波无线通信方案,融合了传感器网络、ARM等工控技术,实现了森林环境参数采集和传输。在系统的总体框架下,重点分析了ZigBee组网的的设计方案,包括软件设计和硬件设计。最后,对节点性能和整个监控系统进行了测试,证明了系统的稳定性和其数据传输的可靠性。     

一种基于GPRS的森林防火远程数据传输系统

针对传统的地面巡防、航空巡防等森林防火监测方法实时性差、监测效果不理想等问题,设计了基于GPRS技术的森林防火远程数据传输系统,硬件采用SIM300模块和单片机,由单片机发送指令控制GPRS工作,GRPS通过网络与上位机进行通信,并将数据上传给上位机.上位机以C++ Builder为开发环境,采用Microsoft SQL Server 2000作为系统的数据库,用C++Builder连接数据库,并实现数据的存储、显示和查询.实验结果表明,该系统能够实时监测森林各项信息数据,能够在很大程度上预防森林火灾的发生.     

基于多传感器数据融合的煤矿采空区火灾预警系统

本文致力于构建一种综合多种传感器信息,并运用数据融合中分层融合思想的煤矿采空区火灾预警系统模型.介绍了传感器性能,设计了火灾监测系统架构,构建了多传感器分层数据融合模型,对采空区遗煤发火阶段状态进行了预测,实验得出了火灾监测系统的主要功能特点.并在火灾区已得到有效治理,实现成功灭火.使防治火灾工作更加合理化和科学化.     

无线火灾监控系统在坑、地道式防护工程中的应用研究

针对目前我国坑、地道式防护工程火灾监测系统存在的问题,设计一种无线火灾监控系统,该系统由传感器节点、路由节点、网关节点以及PC机组成。介绍了该探测系统传感器节点和网关节点的硬件设计以及传感器节点、路由节点、网关节点的功能、流程等软件设计。该系统集监测、显示、报警、通信等多功能于一体,可以对目标区域进行远程监控,监测节点体积小,无需布线,移动、安装方便。     

基于WSN的环境质量监测系统设计与实现

提出、设计并验证了一种低成本、低功耗的分布式环境质量无线实时监测系统。该系统采用基于TI CC2530微控制器的ZigBee无线协议栈。无线采集节点内置的MSP430G2553微控制器收集温湿度传感器、空气微粒传感器和光传感器得到的环境质量数据经由ZigBee无线传感网传送至ZigBee-IP网关。基于S3C2440的嵌入式ZigBee-IP网关将采集到的环境质量数据以Web网页的形式向互联网用户提供实时环境质量报告。该系统针对目前百姓普遍关心的环境质量问题,对于政府环保部门、大型污染企业环境质量监控等有一定的参考及推广价值。     

无线传感器网络中基于监督的安全数据融合方法

In order to avoid internal attacks during data aggregation in wireless sensor networks, a grid-based network architecture fit for monitoring is designed and the algorithms for network division, initialization and grid tree construction are presented. The characteristics of on-off attacks are first studied and monitoring mechanisms are then designed for sensor nodes. A Fast Detection and Slow Recovery (FDSR) algorithm is proposed to prevent on-off attacks by observing the behaviors of the nodes and computing reputations. A recovery mechanism is designed to isolate malicious nodes by identifying the new roles of nodes and updating the grid tree. In the experiments, some situations of on-off attacks are simulated and the results are compared with other approaches. The experimental results indicate that our approach can detect malicious nodes effectively and guarantee secure data aggregation with acceptable energy consumption.     

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

The aim of wireless sensor networks (WSNs) is to gather sensor data from a monitored environment. However, the collected or reported information might be falsified by faults or malicious nodes. Hence, identifying malicious nodes in an effective and timely manner is essential for the network to function properly and reliably. Maliciously behaving nodes are usually detected and isolated by reputation and trust‐based schemes before they can damage the network. In this paper, we propose an efficient weighted trust‐based malicious node detection (WT‐MND) scheme that can detect malicious nodes in a clustered WSN. The node behaviors are realistically treated by accounting for false‐positive and false‐negative instances. The simulation results confirm the timely identification and isolation of maliciously behaving nodes by the WT‐MND scheme. The effectiveness of the proposed scheme is afforded by the adaptive trust‐update process, which implicitly performs trust recovery of temporarily malfunctioning nodes and computes a different trust‐update factor for each node depending on its behavior. The proposed scheme is more effective and scalable than the related schemes in the literature, as evidenced by its higher detection ratio (DR) and lower misdetection ratio (MDR), which only slightly vary with the network's size. Moreover, the scheme sustains its efficient characteristics without significant power consumption overheads.     

Data Aggregation for Increase Performance of Wireless Sensor Networks Using Learning Automata Approach

Wireless sensor networks, a new generation of networks, are composed of a large numbers of nodes and the communication between nodes takes place wirelessly. The main purpose of these networks is collecting information about the environment surrounding the network sensors. The sensors collect and send the required information. There are many challenges and research areas concerned in the literature, one of which is power consumption in network nodes. Nodes in these networks have limited energy sources and generally consume more energy in long communication distances and therefore run out of battery very fast. This results in inefficacy in the whole system. One of the proposed solutions is data aggregation in wireless networks which leads to improved performance. Therefore, in this study an approach based on learning automata is proposed to achieve data aggregation which leads to dynamic network at any hypothetical region. This approach specifies a cluster head in the network and nodes send their data to the cluster head and the cluster head sends the information to the main receiver. Also each node can change its sensing rate using learning automata. Simulation results show that the proposed method increases the lifetime of the network and more nodes will be alive.

     

基于IPv6的WSN图像监控系统的设计与实现

为拓展无线传感器网络的应用,设计并实现了一种基于IPv6无线传感器网络的图像监控系统。系统在IPv6的环境中实现了红外传感器节点控制,图像传感器节点以ARM作为处理器,在嵌入式Linux中设计V4L程序实现采集实时图像,图像汇聚到网关后,网关利用多种Internet接入方式将信息返回到客户端。网络中融合了多种类型的数据,系统分别采用IEEE802.15.4和WiFi方式进行传输,可以提高网络传输效率与可靠性,并能够方便地用于入侵检测等多媒体图像监控方面。     

基于环境信息监测的无线传感器网络节点设计

针对海岸、海洋环境远程实时监测的需求,设计了由超低功耗MCU芯片MSP430F1611、无线收发器芯片CC2420及各种传感器接入电路构成的具有多种环境参数采集功能的无线传感器网络节点.该节点系统利用所搭载的各种传感器采集环境中的温度、湿度、光照强度等数据,通过相邻节点间的无线通信,以多跳传输的方式,将测量数据上传给上...