Fire monitoring in coal mines using wireless underground sensor network and interval type-2 fuzzy logic controller

From the view of underground coal mining safety system, it is extremely important to continuous monitoring of coal mines for the prompt detection of fires or related problems inspite of its uncertainty and imprecise characteristics. Therefore, evaluation and inferring the data perfectly to prevent fire related accidental risk in underground coal mining (UMC) system are very necessary. In the present article, we have proposed a novel type-2 fuzzy logic system (T2FLS) for the prediction of fire intensity and its risk assessment for risk reduction in an underground coal mine. Recently, for the observation of underground coal mines, wireless underground sensor network (WUSN) are being concerned frequently. To implement this technique IT2FLS, main functional components are sensor nodes which are installed in coal mines to accumulate different imprecise environmental data like, temperature, relative humidity, different gas concentrations etc. and these are sent to a base station which is connected to the ground observation system through network. In the present context, a WUSN based fire monitoring system is developed using fuzzy logic approach to enhance the consistency in decision making system to improve the risk chances of fire during coal mining. We have taken Mamdani IT2FLS as fuzzy model on coal mine monitoring data to consider real-time decision making (DM). It is predicted from the simulated results that the recommended system is highly acceptable and amenable in the case of fire hazard safety with compared to the wired and off-line monitoring system for UMC. Legitimacy of the suggested model is prepared using statistical analysis and multiple linear regression analysis.

Energy-Efficient Area Coverage in Heterogeneous Energy Wireless Sensor Networks

Sensing coverage and energy consumption are two primary issues in wireless sensor networks. Sensing coverage is closely related to network energy consumption. The performance of a sensor network depends to a large extent on the sensing coverage, and its lifetime is determined by its energy consumption. In this paper, an energy-efficient Area Coverage protocol for Heterogeneous Energy sensor networks (ACHE) is proposed. ACHE can achieve a good performance in terms of sensing area coverage, lifetime by minimizing energy consumption for control overhead, and balancing the energy load among all nodes. Adopting the hierarchical clustering idea, ACHE selects the active nodes based on the average residual energy of neighboring nodes and its own residual energy parameters. Our simulation demonstrates that ACHE not only provide the high quality of sensing coverage, but also has the good performance in the energy efficiency. In addition, ACHE can better adapt the applications with the great heterogeneous energy capacities in the sensor networks, as well as effectively reduce the control overhead.

A Learning Automata Based Area Coverage Algorithm for Wireless Sensor Networks

One way to reduce energy consumption in wireless sensor networks is to reduce the number of active nodes in the network. When sensors are redundantly deployed, a subset of sensors should be selected to actively monitor the field （referred to as a ＂cover＂）, whereas the rest of the sensors should be put to sleep to conserve their batteries. In this paper, a learning automata based algorithm for energy-efficient monitoring in wireless sensor networks （EEMLA） is proposed. Each node in EEMLA algorithm is equipped with a learning automaton which decides for the node to be active or not at any time during the operation of the network. Using feedback received from neighboring nodes, each node gradually learns its proper state during the operation of the network. Experimental results have shown that the proposed monitoring algorithm in comparison to other existing methods such as Tian and LUC can better prolong the network lifetime.

Localized Coverage Connectivity Based on Shape and Area Using Mobile Sensor Robots in Wireless Sensor Networks

A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works.

A multipath routing protocol for wireless sensor network for mine security monitoring

Underground mining is a hazardous industrial activity. In order to provide a safe working environment for miners, a Wireless Sensor Network (WSN) technology has been used for security monitoring. It can provide a wide range of surveillance with a relatively low cost. In this study, an Energy-Based Multipath Routing (EBMR) protocol is proposed, which considers residual energy capacity and link quality in choosing hops and routing paths. Hops and paths with a high residual energy capacity and link quality will have the best chance to be selected to transmit data packages. Since the EBMR stores several routes in the routing table, when the current path fails, another path will be chosen to fulfill the task immediately. In this way, EBMR improves reliability and decrease time latency. Compared to AOMDV and REAR, EBMR decreases time latency by 51% and 12%.

A novel nest-based scheduling method for mobile wireless body area networks

Wireless Body Area Networks(WBANs)comprise various sensors to monitor and collect various vital signals,such as blood pressure,pulse,heartbeat,body temperature,and blood sugar.A dense and mobile WBAN often suffers from interference,which causes serious problems,such as wasting energy and degrading throughput.In reality,not all of the sensors in WBAN need to be active at the same time.Therefore,they can be divided into different groups so that each group works in turn to avoid interference.In this paper,a Nest-Based WBAN Scheduling(NBWS)algorithm is proposed to cluster sensors of the same types in a single or multiple WBANs into different groups to avoid interference.Particularly,we borrow the graph coloring theory to schedule all groups to work using a Time Division for Multimodal Sensor(TDMS)group scheduling model.Both theoretical analysis and experimental results demonstrate that the proposed NBWS algorithm performs better in terms of frequency of collisions,transmission delay,system throughput,and energy consumption compared to the counterpart methods.

An immune-swarm intelligence based algorithm for deterministic coverage problems of wireless sensor networks

A novel immune-swarm intelligence (ISI) based algorithm for solving the deterministic coverage problems of wireless sensor networks was presented.It makes full use of information sharing and retains diversity from the principle of particle swarm optimization (PSO) and artificial immune system (AIS).The algorithm was analyzed in detail and proper swarm size,evolving generations,gene-exchange individual order,and gene-exchange proportion in molecule were obtained for better algorithm performances.According to the test results,the appropriate parameters are about 50 swarm individuals,over 3 000 evolving generations,20%-25% gene-exchange proportion in molecule with gene-exchange taking place between better fitness affinity individuals.The algorithm is practical and effective in maximizing the coverage probability with given number of sensors and minimizing sensor numbers with required coverage probability in sensor placement.It can reach a better result quickly,especially with the proper calculation parameters.

A Review of Wireless Body Area Networks for Medical Applications

Recent advances in Micro-Electro-Mechanical Systems (MEMS) technology, integrated circuits, and wireless communication have allowed the realization of Wireless Body Area Networks (WBANs). WBANs promise unobtrusive ambulatory health monitoring for a long period of time, and provide real-time updates of the patient’s status to the physician. They are widely used for ubiquitous healthcare, entertainment, and military applications. This paper reviews the key aspects of WBANs for numerous applications. We present a WBAN infrastructure that provides solutions to on-demand, emergency, and normal traffic. We further discuss in-body antenna design and low-power MAC protocol for a WBAN. In addition, we briefly outline some of the WBAN applications with examples. Our discussion realizes a need for new power-efficient solu-tions towards in-body and on-body sensor networks.

A Sensor Awakening Algorithm for Wireless Multimedia Sensor Networks Three Dimensional Target Tracking

For node awakening in wireless multi-sensor networks, an algorithm is put forward for three dimensional tar- get tracking. To monitor target dynamically in three dimensional area by controlling nodes, we constract vir- tual force between moving target and the current sense node depending on the virtual potential method, then select the next sense node with information gain function, so that when target randomly move in the specific three dimensional area, the maximum sensing ratio of motion trajectory is get with few nodes. The proposed algorithm is verified from the simulations.

An Application-Oriented Network Model for Wireless Sensor Networks

Wireless sensor networks (WSNs) are energy-constrained networks. The residual energy real-time monitoring (RERM) is very important for WSNs. Moreover, network model is an important foundation of RERM research at personal area network (PAN) level. Because RERM is inherently application-oriented, the network model adopted should also be application-oriented. However, many factors of WSNs applications such as link selected probability and ACK mechanism etc. were neglected by current network models. These factors can introduce obvious influence on throughput of WSNs. Then the energy consumption of nodes will be influenced greatly. So these models cannot characterize many real properties of WSNs, and the result of RERM is not consistent with the real-world situation. In this study, these factors neglected by other researchers are taken into account. Furthermore, an application-oriented general network model (AGNM) for RERM is proposed. Based on the AGNM, the dynamic characteristics of WSNs are simulated. The experimental results show that AGNM can approximately characterize the real situation of WSNs. Therefore, the AGNM provides a good foundation for RERM research.

An Efficient Billing Scheme for Trusted Nodes Using Fuzzy Logic in Wireless Sensor Networks

Extending the lifetime of the wireless sensor networks (WSNs), where recharging sensors is not always possible, has been a major concern for researchers for the past decade. In this paper, we study the cooperation between nodes in wireless sensor networks in forwarding packets to others, and we propose a new collaboration technique which stimulates intermediate nodes to forward packets toward their destination. Some nodes show selfish behavior by denying the forwarding packets to other nodes in commercial networks in an effort to preserve their own energy. This paper applies a technique which is used to prolong the network lifetime, based on a node’s energy and trust value, and additionally incorporates fuzzy logic, which stimulates nodes to forward packets by rewarding cooperation. According to simulation results, the proposed approach surpasses the Nuglets (virtual currency) approach and the Reputation approach in network energy and thus prolongs the network lifetime. Additionally, our proposed approach demonstrates better results in the number of dropped packets, PDR and forwarded packets to neighboring nodes.

Ultra-Low Power 1 Volt Small Size 2.4 GHz CMOS RF Transceiver Design for Wireless Sensor Node

Ultra-low power transceiver design is proposed for wireless sensor node used in the wireless sensor network（WSN）.Typically,each sensor node contains a transceiver so it is required that both hardware and software designs of WSN node must take care of energy consumption during all modes of operation including active/sleep modes so that the operational life of each node can be increased in order to increase the lifetime of network.The current declared size of the wireless sensor node is of millimeter order,excluding the power source and crystal oscillator.We have proposed a new 2.4 GHz transceiver that has five blocks namely XO,PLL,PA,LNA and IF.The proposed transceiver incorporates less number of low-drop outs（LDOs）regulators.The size of the transceiver is reduced by decreasing the area of beneficiary components up to 0.41 mm;of core area in such a way that some functions are optimally distributed among other components.The proposed design is smaller in size and consumes less power,<1 mW,compared to other transceivers.The operating voltage has also been reduced to 1 V.This transceiver is most efficient and will be fruitful for the wireless networks as it has been designed by considering modern requirements.

A Review of Quantum Cryptography Communication for Wireless Networks

We analyze the development of quantum cryptography communication,including analyze the problems lie in the existent literatures and give the resolve methods according to these problems.Then discuss the quantum cryptography communication for wireless networks and also point out the shortcoming of current research and the future of quantum wireless networks.

An energy efficiency clustering routing protocol for WSNs in confined area

Wireless sensor networks (WSNs) are important application for safety monitoring in underground coal mines, which are difficult to monitor due to natural conditions. Based on the characteristic of limited energy for WSNs in confined underground area such as coal face and laneway, we presents an energy- efficient clustering routing protocol based on weight (ECRPW) to prolong the lifetime of networks. ECRPW takes into consideration the nodes' residual energy during the election process of cluster heads. The constraint of distance threshold is used to optimize cluster scheme. Furthermore, the protocol also sets up a routing tree based on cluster heads' weight. The results show that ECRPW had better perfor- mance in energy consumption, death ratio of node and network lifetime.

Area Query Processing Based on Gray Code in Wireless Sensor Networks

Area query processing is significant for various applications of wireless sensor networks since it can request information of particular areas in the monitored environment. Existing query processing techniques cannot solve area queries. Intuitively, centralized processing on Base Station can accomplish area queries via collecting information from all sensor nodes. However, this method is not suitable for wireless sensor networks with limited energy since a large amount of energy is wasted for reporting useless data. This motivates us to propose an energy-efficient in-network area query processing scheme. In our scheme, the monitored area is partitioned into grids, and a unique gray code number is used to represent a Grid ID （GID）, which is also an effective way to describe an area. Furthermore, a reporting tree is constructed to process area merging and data aggregations. Based on the properties of GIDs, subareas can be merged easily and useless data can be discarded as early as possible to reduce energy consumption. For energy-efficiently answering continuous queries, we also design an incremental update method to continuously generate query results. In essence, all of these strategies are pivots to conserve energy consumption. With a thorough simulation study, it is shown that our scheme is effective and energy-efficient

Sensor selection for parameterized random field estimation in wireless sensor networks

We consider the random field estimation problem with parametric trend in wireless sensor networks where the field can be described by unknown parameters to be estimated. Due to the limited resources, the network selects only a subset of the sensors to perform the estimation task with a desired performance under the D-optimal criterion. We propose a greedy sampling scheme to select the sensor nodes according to the information gain of the sensors. A distributed algorithm is also developed by consensus-based incremental sensor node selection through information quality computation for and message exchange among neighboring sensors. Simulation results show the good performance of the proposed algorithms.

Using Wearable Sensors for Remote Healthcare Monitoring System

Recent technological advances in wireless communications and wireless sensor networks have enabled the design of low-cost, intelligent, tiny, and lightweight medical sensor nodes that can be strategically placed on human body, create a wireless body area network (WBAN) to monitor various physiological vital signs for a long period of time and providing real-time feedback to the user and medical staff. WBANs promise to revolutionize health monitoring. In this paper, medical sensors were used to collect physiological data from patients and transmit it to Intelligent Personal digital Assistant (IPDA) using ZigBee/IEEE802.15.4 standard and to medical server using 3G communications. We introduced priority scheduling and data compression into the system to increase transmission rate of physiological critical signals which improve the bandwidth utilization. It also extends the life time of hand-held personal server by reducing power consumption during transmission.

Unweighted Voting Method to Detect Sinkhole Attack in RPL-Based Internet of Things Networks

The Internet of Things(IoT)consists of interconnected smart devices communicating and collecting data.The Routing Protocol for Low-Power and Lossy Networks(RPL)is the standard protocol for Internet Protocol Version 6(IPv6)in the IoT.However,RPL is vulnerable to various attacks,including the sinkhole attack,which disrupts the network by manipulating routing information.This paper proposes the Unweighted Voting Method(UVM)for sinkhole node identification,utilizing three key behavioral indicators:DODAG Information Object(DIO)Transaction Frequency,Rank Harmony,and Power Consumption.These indicators have been carefully selected based on their contribution to sinkhole attack detection and other relevant features used in previous research.The UVM method employs an unweighted voting mechanism,where each voter or rule holds equal weight in detecting the presence of a sinkhole attack based on the proposed indicators.The effectiveness of the UVM method is evaluated using the COOJA simulator and compared with existing approaches.Notably,the proposed approach fulfills power consumption requirements for constrained nodes without increasing consumption due to the deployment design.In terms of detection accuracy,simulation results demonstrate a high detection rate ranging from 90%to 100%,with a low false-positive rate of 0%to 0.2%.Consequently,the proposed approach surpasses Ensemble Learning Intrusion Detection Systems by leveraging three indicators and three supporting rules.

面向智能电网广域通信的可靠路由算法研究

无线传感器网络是智能电网广域通信中的基础组成单元,传统的无线传感器网络分簇路由协议虽能在一定程度上简化网络拓扑,但仍存在簇首选择不合理且系统能耗较高的问题。针对此,文中基于粒子群优化算法提出了一种改进的分簇路由协议。该协议利用粒子群算法的参数寻优特性对簇首搜寻方案加以改进,使得新方案考虑了距离、剩余能量、数据传输精度等多种因素。同时还使用粒子群自适应函数对该方案进行优化,从而提高了原算法的可靠性。在能耗实验测试中,所提算法迭代1 300次后的剩余能耗为31.2 J,在对比算法中为最优。而对路由路径的测试中,改进算法的平均运行时延为1.79 ms,平均误码率为0.212 5,在所有算法中均为最低,证明了该算法具有良好的实时性和可靠性。

基于组合加权k近邻分类的无线传感网络节点复制攻击检测方法

无线传感网络节点体积小,隐蔽性强,节点复制攻击检测的难度较大,为此提出一种基于组合加权k近邻分类的无线传感网络节点复制攻击检测方法。通过信标节点的空间位置数据与相距跳数得出各节点之间的相似程度,结合高斯径向基核函数求解未知节点的横轴、纵轴的空间坐标,确定各网络节点的空间位置;根据网络节点的属性特征与投票机制建立节点复制攻击模型,凭借组合加权k近邻分类法划分节点类型,并将结果传送至簇头节点,由簇头节点做出最后的仲裁,识别出节点复制攻击行为。仿真结果表明,所提方法的节点复制攻击检测率最大值为99.5%,最小值为97.9%,对节点复制攻击检测的耗时为5.41 s,通信开销数据包数量最大值为209个,最小值为81个。