Wireless sensor networks wsns have been used in various domains such as military applications e. Data fusion technology compresses the sampled data to eliminate redundancy, which can effectively reduce the amount of data sent by the node and prolong the lifetime of the. We first divided the sensor field into several equal. Section 4 presents some highlevel protocols for energye. Pdf study of data fusion in wireless sensor network. Mac protocol for wireless sensor networks must consume little power, avoid collisions, be implemented with a small code size and memory requirements, be e. Proceedings of 2010 uk workshop on computational intelligence. In wireless sensor networks, resourceconstrained sensor nodes are spread over a potentially large area to measure environmental characteristics such as. Extending lifetime of wireless sensor networks using multi. For a wireless sensor network wsn with a random number of sensors, we propose a decision fusion rule that uses the total number of detections reported by local sensors as a statistic for hypothesis testing. Pdf a data fusion method in wireless sensor networks. Synchronization of multiple levels of data fusion in wireless. Decision fusion rules in wireless sensor networks using fading channel statistics ruixin niu, biao chen, and pramod k.
Security mechanism of transmission encryption of network is introduced to protect the security of data. Research on wireless sensor networks data fusion algorithm. Data fusion with desired reliability in wireless sensor. However, with the continuous application of wireless sensor networks, it raises higher demands for information integrity and privacy, data fusion faces new challenges. Introduction wireless sensor networks is an emerging technology that is gaining a lot of attention for applications such as monitoring and data gathering.
Wireless sensor networks introduction to wireless sensor networks february 2012 a wireless sensor network is a selfconfiguring network of small sensor nodes communicating among themselves using radio signals, and deployed in quantity to sense, monitor and understand the physical world. Lemma1 the conditional pdf of y k, the observation from sensor k, given the local decision u. This paper studies the data fusion of the industrial wireless sensor networks iwsns, in order to acquire more thoughtful data for the prognosis and diagnosis of the monitored device. Data fusion in wireless sensor networks using fuzzy systems. Wireless multiple access schemes, where correlated signals, observed at different nodes, need to be transferred to one or more collectors, model several communication scenarios. To improve the wireless sensor networks data fusion efficiency and reduce network traffic and the energy consumption of sensor networks, combined with chaos optimization algorithm and bp algorithm designed a chaotic bp hybrid algorithm coabp, and establish a wsns data fusion model. To avoid these above disadvantages, a trust evaluation model based on the autonomous behavior of sensor node is proposed in this paper. Dynamic data fusion for future sensor networks umakishore ramachandran, rajnish kumar, matthew wolenetz, brian cooper, bikash agarwalla, junsuk shin, phillip hutto, and arnab paul college of computing, georgia institute of technology dfuse is an architectural framework for dynamic applicationspeci. Data acquisition and fusion system based on wireless sensor dan qiu1, shuli gong2. Data fusion in wireless sensor networks maen takruri submitted in partial fulfillment of the requirements for the degree of doctor of philosophy faculty of engineering and inforrnation technology university of technology, sydney march 2009.
Wireless sensor networks technology and applications. If these redundant data are processed and transmitted, the node energy consumption will be too fast and will affect the overall lifetime of the network. For example, these schemes apply to wireless sensor networks, where a set of nodes collect and transmit correlated data to a common sink in an energyef. It is now possible to construct, from commercial o theshelf cots com. In figure 3, the osi model is used in this article to compare the two wsn standards. A large number of sampling data of damage response signal will cause huge wireless communication burden. Evolution of wireless sensor networks for industrial control arthur low the rio through any b and r node. We show that data fusion can significantly improve sensing. In addition, the gating technique is also applied to solve the problem of msdft mobilesensor data fusion tracking for targets, i. A data fusion method in wireless sensor networks ncbi.
Wireless sensor data fusion algorithm based on the sensor. One the computational intelligence algorithms is fuzzy logic or fuzzy system algorithm. Multiorder fusion data privacypreserving scheme for wireless. Challenges in wireless sensor network wireless sensor network assure a wide variety of. A data fusion method in wireless sensor networks mdpi. The paper focuses on issues related to the integration of wireless sensor network security data, analyzes its attack types. Data fusion based on distributed quality estimation in.
Distributed signal processing and data fusion methods for. Evolution of wireless sensor networks for industrial control. Wireless sensor networks wsns can be defined as a selfconfigured and infrastructureless wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or sink where the data can be observed and analysed. Wireless sensor networks consist of a powerful technology for monitoring the physical world. Pdf similarity clustering for data fusion in wireless. Research on data fusion scheme for wireless sensor. Extending lifetime of wireless sensor networks using multisensor data fusion soumitra das1, s barani2, sanjeev wagh3 and s s sonavane4 1department of computer science and engineering, sathyabama university, chennai 600119, india 2department of electronics and control engineering, sathyabama university, chennai 600119, india 3department of computer engineering, k.
Multisensors data fusion system for wireless sensors. The data fusion at various levels should be synchronized in. A new data fusion algorithm for wireless sensor networks. In this article, we use a neural network to help set up a wsn with distributed data fusion. Based on the analysis of typical application scenarios in traffic field and the. Data fusion improves the coverage of wireless sensor.
A new data fusion algorithm for wireless sensor networks inspired. Each sensor node has the monitoring privilege and obligation. Data fusion and collaborative state estimation in wireless sensor networks. Data fusion utilization for optimizing largescale wireless sensor networks mohammadreza soltani, michael hempel, hamid sharif advanced telecommunications engineering laboratory, dept. In our prior work 2, while a randomized algorithm termed minimum fusion steiner tree mfst is devised towards this end, it assumes that data fusion shall be. Data fusion in wireless sensor networks a statistical. Adaptive decision fusion with a guidance sensor in wireless sensor networks zhaohuayu,1 qiangling,1 andyiyu2. Manets have high degree of mobility, while sensor networks are mostly stationary. Energy efficient data fusion in wireless sensor networks are necessary because, the sensor nodes are battery operated, and it is important to keep track of the energy issues 12. Decision fusion in a wireless sensor network with a large. Since it is impossible to confirm that the collected data are true values of the events without taking samples or analyzing data history, we suggest assigning a weight for each collected data.
The success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. A study on data fusion of wireless sensor networks. Multimedia data fusion method based on wireless sensor. Data fusion improves the coverage of wireless sensor networks. In this paper, we present a fuzzybased data fusion approach for wsn with the aim of increasing the qos whilst reducing the energy consumption. Wireless sensor networks can be used to monitor the condition of civil infrastructure and related geophysical processes close to real time, and over long periods through data logging, using appropriately interfaced sensors. This paper discusses about wireless sensor network, its. Adaptive decision fusion with a guidance sensor in. Nakamura analysis, research and technological innovation center fucapi federal university of minas gerais ufmg antonio a. Wireless sensor networks, routing topology, network inference, compressed sensing, recovery algorithms. Data fusion with desired reliability in wireless sensor networks abstract.
Synchronization of multiple levels of data fusion in. In order to realize the ubiquitous perception of urban traffic system integration, a universal technology architecture supporting multiple heterogeneous access, universalization and tailoring is needed to realize the interconnection and interoperability of perception systems in different application scenarios. Data aggregation is necessary for wireless sensor networks. Sensor fusion helps in building a more accurate world model in order for the robot to navigate and behave more successfully. In this research study, an energy efficient cluster head selection in mobile wireless sensor networks is proposed, analysed and validated on the basis of residual energy and randomized selection. Wireless sensor networks wsns consist of large number of constrained wireless sensor nodes for the purpose of data gathering. We propose a deep learning architecture for the sensor fusion problem that consists of two convolutional neural networks cnns, each consisting of a different input modality, which are fused with a gating mechanism. Wireless sensor networks, distributed detection, decision fusion, signal attenuation model. For the sake of avoiding the data abundance and balancing the energy consumption in wireless sensor networks, a data fusion clustering hierarchy based on data fusion chdf is proposed.
Routing topology inference for wireless sensor networks. Sensor modality fusion with cnns for ugv autonomous. Sensor fusion is the process of merging data from multiple sensors such that to reduce the amount of uncertainty that may be involved in a robot navigation motion or task performing. As data either raw or fused is propagated towards the sink, multiple levels of data fusion are likely. Physiological signal acquisition system based on wireless sensor networks. Distributed sequential estimation in asynchronous wireless sensor networks ondrej hlinka, franz hlawatsch, fellow, ieee,andpetarm. Introduction recent years have witnessed the deployments of wireless sensor networks wsns for many critical applications such as security surveillance 16, environmental monitoring 25, and target detectiontracking 21. Therefore, to maximize the lifetime of sensor networks, aggressive energy optimization techniques have to be used for ensuring that energy is conserved for the sensor nodes. Following the latest developments in computer and communication technologies, everyday objects are becoming smarter, as ubiquitous connectivity and modern sensors allow them to communicate with each other.
Many conventional methods in various sciences are not able to properly support a high volume of quantitative and qualitative information 8. Systemlevel calibration for data fusion in wireless sensor. This investigate is to finish the factory monitoring at environment monitoring services ems. Distributed fusion of sensor data in a constrained.
The sensor nodes sns compute local decisions about the intruders presence and send them to the cluster heads chs. Due to the limitations of some sensor nodes, especially the limited amount of energy, in network data processing, such as data fusion, is very important. Data fusion based on node trust evaluation in wireless sensor. Related issues study of wireless sensor network security. Optimal fusion rule for distributed detection in clustered. Pdf the success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding issues such as. These authors propose a combination of back propagation neural. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. A stochastic geometry framework is employed to derive the.
Efficient multisource data fusion for decentralized sensor networks unclassifiedunlimited if nodes a and b communicate their information, the updated estimate can be calculated as the product of their distributions divided by the common information 12. Pdf data fusion techniques in wireless sensor networks. These computers typically called motes or sensor nodes are equipped with di erent types of sensors, such as e. Recent advances insemiconductor, networking and material science technologies are driving the ubiquitous deployment of largescale wireless sensor networks wsns. Sensor networks although fusion frames can be used to model general distributed processing applications, in this paper we intend to focus on the modeling of sensor networks.
Many practical wireless sensor networks have multiple sensor modalities 26. The book highlights power efficient design issues related to wireless sensor networks, the existing wsn applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and. Deddistance energy and degree, wireless sensor networks i. Wireless sensor networks wsn provide a bridge between the real physical and virtual worlds allow the ability to observe the previously unobservable at a fine resolution over large spatiotemporal scales have a wide range of potential applications to industry, science, transportation, civil infrastructure, and security. An intelligent data gathering schema with data fusion supported for. Since the sensor nodes are battery operated, collecting and transmitting data will cost a lot of energy resources. Pdf on jun 1, 2018, mahnaz koupaee and others published data fusion techniques in wireless sensor networks. Generally, a large number of sensor nodes, capable of collecting data, processing and communicating. Data fusion based on node trust evaluation in wireless. The isa network also shows a backbone network solid thick line connecting the gms and the backbone routers.
This study attempts to apply a backpropagation network bpn for multisensors data fusion in a wireless sensor networks wsns system with a nodesink mobile network structure. Abnormal behavior detection and trust evaluation mode of traditional sensor node have a single function without considering all the factors, and the trust value algorithm is relatively complicated. Section 5 present existing data fusion techniques in wireless sensor networks. In typical wireless sensor networks, sensor nodes are usually limited in resources and energy. The loss of battery or energy may lead to failure of the entire network 14. Impact of data fusion on realtime detection in sensor. The captured image at the source could be noisy, incomplete and redundant. Abstractin wireless sensor networks, innetwork data fusion is needed for energyef. Index terms sensor networks, data gathering, data fusion. Introduction wireless sensor networks wsns have been fundamentally changing todays practice of numerous scienti.
The wsn is modeled by a homogeneous poisson point process. Based on the management pattern of cluster structure, in 1, conti et al. But in the structural health monitoring based on wireless sensor networks, this method has some inevitable defects in data transmission. Particularly, in network data fusion techniques are very important to applications such as target. Image fusion forwireless sensor networks abstractmajor source of energy consumption in wireless sensor networks wsnsis transmission of image from source to sink and image processing at the nodes. Data fusion technology is widely used in data processing due to its characteristic of less transfer data. Wireless sensor networks wsns are resourceconstrained networks, especially when the energy is highly constrained. We assume that the signal power attenuates as a function of the distance from the target, the number of sensors follows a poisson distribution, and the locations of sensors follow a.
Data fusion of wireless sensor network for prognosis and. Wireless sensor networks are typically composed of lowcost sensors that are deeply integrated in physical environments. Fuzzy data fusion for fault detection in wireless sensor networks. Design and deployment of wsn in a home environment and real. Data fusion in wireless sensor networks ieee conference. A study on data fusion of wireless sensor networks security. Sections 2 and 3 provide examples of mac and network protocols, respectively, for use in sensor networks. Data fusion in wireless sensor networks yun liu, qingan. With the promotion of the latest technologies and the new requirement of humanitarian, the wireless multisensor system is applied broadly. Data fusion is a powerful tool for wireless sensor networks in many aspects, such as energy saving, target coverage, routing algorithm, data dissemination and so.
The aim of this book is to present few important issues of wsns, from the application, design and technology points of view. With the feature of large amount of data for wireless sensor networks, high data redundancy and low energy of nodes, we propose the sensor nodes data fusion algorithm based on. Saad, nasrullah armi, nidal kamel abstractduring the last decades. Abstractwireless sensor networks consist of a large number sensor nodes that are deployed in some geographical area. In order to reduce the data processing load on bs and efficiently distinguish the authenticity of archived data, izadi et al. Efficient multisource data fusion for decentralized. Wireless sensor networks wsn have gained much attention recently. Abstract wireless sensor networks consist of a large number sensor nodes that are deployed in some geographical area. Data acquisition and fusion system based on wireless sensor. Analytically and experimentally, we show that afst achieves better performance than existing algorithms including slt, spt, and mfst. Distributed detection and fusion in a large wireless. A survey wireless sensor networks wsns consist of small nodes with sensing, computation, and wireless communications capabilities. One example of a good mac protocol for wireless sensor networks is bmac 24.
The gating mechanism is realized as a fullyconnected network. Data fusion in wireless sensor networks wsns can improve the performance of a network by eliminating redundancy and power consumption, ensuring faulttolerance between sensors, and managing. Together, these technologies have combined to enable a new generation of wsns that differ greatly from wireless networks developed. In 27, a surveillance system has both lowend passive infrared sensors and highquality. Data fusion can effectively reduce the volume of data transmission in the network, reduce the energy consumption to extend network lifetime and improve bandwidth utilization, as a result, it can overcome.
To save more energy, innetwork processing such as data fusion is a widely used technique, which, however, may often lead to unbalanced information among nodes. Data fusion, target detection, coverage, performance limits, wireless sensor network 1. Due to the limitations of some sensor nodes, especially the limited amount of energy, innetwork data processing, such as data fusion, is very important. Energyefficient and reliable transmission of sensory information is a key problem in wireless sensor networks. Usually a wsn consists of a large number of lowcost and lowenergy sensors, which are deployed in the environment to collect observations and preprocess the. There are a lot of redundant data in wireless sensor networks wsns. The role of data fusion has been expanding in recent years through the incorporation of pervasive applications, where the physical infrastructure is coupled with information and communication technologies, such as wireless sensor networks for the internet of things iot, ehealth and industry 4. Due to the advantage of data fusion in deleting redundant information and extending lifetime of network, data fusion has become one of the important ways of effectively relieving the bottleneck of wireless sensor networks resources, which has been widely used in wireless sensor networks. The application of these methods, however, requires some care due to a number of issues that are particular to sensor networks. We consider distributed detection in a clustered wireless sensor network wsn deployed randomly in a large field for the purpose of intrusion detection. Data fusion methods data compression wireless sensor network.
Data fusion and topology control in wireless sensor networks. In this paper an algorithm of data fusion to track both of nonmaneuvering and maneuvering targets with mobile sensors deployed in an wsn wireless sensor network is proposed and investigated. A data fusion method in wireless sensor networks article pdf available in sensors 152. Data fusion techniques for auto calibration in wireless. We derive the scaling laws between coverage, network density, and signalto noise ratio snr. The objective is to maximize the network lifetime equation 4 ensuring that the percentage of the true value of data and data redundancy are satisfied by a userdefined value equation 5. Compressive sampling and data fusionbased structural damage. Data fusion and collaborative state estimation in wireless. When a sensor node sends out a packet, it puts the residual energy e r in the header file of the data packet to convey the information to the neighbor nodes. Impact of data fusion on realtime detection in sensor networks rui tan 1guoliang xing2 benyuan liu3 jianping wang 1city university of hong kong, hksar 2michigan state university, usa 3university of massachusetts lowell, usa abstractrealtime detection is an important requirement of many missioncritical wireless sensor network applications. Isbn 97839026523, pdf isbn 9789535158394, published 20090201. Wireless communications and mobile computing wirel. Fellow, ieee abstractwe propose a distributed sequential estimation scheme for wireless sensor networks with asynchronous measurements.
Section 6 justifies the need for energy efficient data fusion. Data fusion in mobile wireless sensor networks muhammad arshad, member, iaeng, mohamad alsalem, farhan a. Wireless sensor networks may be considered a subset of mobile adhoc networks manet. Wsn nodes have less power, computation and communication compared to manet nodes. Data fusion improves the coverage of wireless sensor networks december 9, 2010 embedded staff recent years have witnessed the deployments of wireless sensor networks wsns for many critical applications such as security surveillance, environmental monitoring, and target detectiontracking. Wireless sensor network sensor data elderly person smart home current. Information fusion in wireless sensor networks with source. We also explain each of the parameters in much more detail lines 434481. Distributed sequential estimation in asynchronous wireless. Methods, models, and classifications nakamura, loureiro, frery 2 enabling robotic attitude sensing and autonomous navigation through inertial sensor technology david churchill 2010. Chief of among these are the distributed nature of computation and deployment coupled with communications bandwidth and energy constraints typical of many sensor networks. Loureiro federal university of minas gerais ufmg and alejandro c.