Data fusion approach for error correction in wireless sensor. Data fusion based on node trust evaluation in wireless. The success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding issues. Quality estimation based data fusion in wireless sensor networks. Wireless sensor networks wsns consist of large number of constrained wireless sensor nodes for the purpose of data gathering. Synchronization of multiple levels of data fusion in wireless sensor networks wei yuan, srikanth v. China xue liu, mcgill university, canada jianguo yao, shanghai jiao tong university, p. Multisensors data fusion system for wireless sensors. 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. Wsn nodes have less power, computation and communication compared to manet nodes. Introduction a wireless sensor network is a network which comprises. Sensor fusion is also known as multi sensor data fusion and is a subset of information fusion. 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.
The proposed algorithm can greatly increase the safety and accuracy of data fusion, improve communication efficiency, save energy of sensor node, suit different application fields, and deploy environments. This dataset contains temporal data from a wireless sensor network worn by an actor performing the activities. Data fusion approach for error correction in wireless. A fuzzy data fusion solution to enhance the qos and the energy. This paper describes the application of bpn technology in the problem domain of sensor data fusion. Data fusion based on node trust evaluation in wireless sensor.
Developing a fusion application is challenging in general, for the fusion operation typically requires timecorrelation and synchronization of data streams coming from several distributed sources. In this paper, we have presented a fuzzybased method for data fusion. 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. Scalable structurefree data fusion on wireless sensor. Synchronization of multiple levels of data fusion in wireless. 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. Keywords wsn, data aggregation, data fusion, sensor network, iot i. 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. Moreover, if there is no possibility to fuse data in the head node, it must send a lot of packets towards.
Data fusion in wireless sensor networks using fuzzy systems. Manets have high degree of mobility, while sensor networks are mostly stationary. As an important element of internet of things, wireless sensor networks wsn are composed of many compact microsensors. Pdf a data fusion method in wireless sensor networks. In proceedings of the 4th international conference on networking icn 2005, p. A strategy for avoiding energy holes based on data fusion. Data fusion and topology control in wireless sensor networks. Systemlevel calibration for data fusion in wireless. Research article secure data fusion in wireless multimedia sensor networks via compressed sensing ruigao, 1,2 yingyouwen, 1,2 andhongzhao 1,2 college of information science and engineering, northeastern university, shenyang, china. This paper focuses on the challenges involved in supporting fusion applications in wireless ad hoc sensor networks wasn. Extending lifetime of wireless sensor networks using multi.
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. Pdf study of data fusion in wireless sensor network. Tripathi department of computer science and engineering, university of california, riverside, riverside, ca, 92521 abstractin wireless sensor networks, innetwork data fusion. Wireles sensor network diagram download read online. Research on the wireless sensor network data fusion technology. A strategy for avoiding energy holes based on data fusion in wireless sensor network p. To save more energy, in network processing such as data fusion is a widely used technique, which, however, may often lead to unbalanced information among nodes in the data fusion tree. Wireless sensor networks wsns are formed of various nodes that gather parameters in a monitored environment. Data fusion techniques for auto calibration in wireless. In this paper a multisensor data fusion approach for wireless sensor network based on bayesian methods and ant colony optimization. We propose a system for wsn applications that allows to assess the quality of sensor data and further allows to fuse data based on their estimated quality.
Wireless sensor networks wsns are resourceconstrained networks, especially when the energy is highly constrained. We are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including nobel prize winners and some of. 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. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and history values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input. Multi sensor data fusion in wireless sensor network using pdf. Energyefficient data fusion technique and applications in. 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. Security mechanism of transmission encryption of network is introduced to protect the security of data. Research on the wireless sensor network data fusion. In wireless sensor networks, using the data fusion at different. An algorithm of mobile sensors data fusion tracking for. 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.
This paper highlights the advantages of data fusion and topology control in wireless sensor networks. Extending lifetime of wireless sensor networks using multisensor. Resourceaware data fusion algorithms for wireless sensor. The wireless sensor network wsn is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. A robust location algorithm with biased extended kalman filtering of tdoa data for wireless sensor networks. As the communication consumes a significant part of the energy in wireless networks, ordinary parallel data fusion approaches may expend more energy than serial data fusion techniques, due to the fact that all sensed data is sent to a central node.
Timeselective data fusion for innetwork processing in ad hoc. Energyefficient and reliable transmission of sensory information is a key problem in wireless sensor networks. Activity recognition system based on multisensor data fusion arem data set download. Information fusion for data dissemination in selforganizing wireless sensor networks. Jan 28, 2015 handling sensing data errors and uncertainties in wsn while maximizing network lifetime are important issues in the design of applications and protocols for wireless sensor networks. A new data fusion algorithm for wireless sensor networks inspired. Wireless sensor networks are used to monitor wine production, both in the field and the cellar. Pdf the success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding. Due to the limitations of sensor nodes capabilities, especially the strictly limited energy, innetwork data processing, such as data fusion which can significantly improve the.
Wireless sensor networks wsns consist of a large number of source limited wireless sensor nodes for the purpose of data collection, processing, and transmission. The captured image at the source could be noisy, incomplete and redundant. A peertopeer collaboration framework for multisensor. China wireless sensor networks are typically composed of lowcost sensors that are deeply integrated. Data fusion methods data compression wireless sensor. The loss of battery or energy may lead to failure of the entire network 14. In addition, the desired accuracy in the result of the multisensor fusion has to be obtained by selecting a proper set of data from multiple.
Data fusion privacy preserving algorithm based on failure. Alexandre ciancio, sundeep pattem, antonio ortega, bhaskar krishnamachari, energyefficient data representation and routing for wireless sensor networks based on a distributed wavelet compression algorithm, proceedings of the 5th international conference on information processing in sensor networks, april 1921, 2006, nashville, tennessee. Data fusion improves the coverage of wireless sensor. Wireless sensor networks a survey on monitoring water. Data fusion methods free download as powerpoint presentation. In the multisensor data fusion, data needs to be combined in such a manner that the realtime requirement of the sensor application is met. Activity recognition system based on multisensor data fusion. Energy holes problem is one of key issues for wireless sensor networks wsn. Synchronization of multiple levels of data fusion in.
Nakamura analysis, research and technological innovation center fucapi federal university of minas gerais ufmg antonio a. Data fusion methods data compression wireless sensor network. 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. The wireless sensor network wsn is mainly composed of a large number of sensor nodes that are equipped with limited energy and. In proceedings of the international conference on wireless communications, networking and mobile computing wcnm05. Data fusion, target detection, coverage, performance limits, wireless sensor network 1. While innetwork data fusion can reduce data redundancy andhence curtail network load, the fusion process itself may introduce significant energy consumption for emerging wireless sensor networks with vectorial data. 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.
Data fusion in sensors is defined as the process 1. Scalable structurefree data fusion on wireless sensor networks. However, some costs are incurred by nonuniform node distribution. Wireless sensor networks may be considered a subset of mobile adhoc networks manet. Manet wireless sensor networks may be considered a subset of mobile adhoc networks manet. Abstract wireless sensor networks consist of a large number sensor nodes that are deployed in some geographical area. Pdf data fusion techniques in wireless sensor networks. Handling sensing data errors and uncertainties in wsn while maximizing network lifetime are important issues in the design of applications and protocols for wireless sensor networks. Zhai et al 4 proposed an algorithm space wireless sensor networks for planetary exploration swipe, where two types of data are processed separately in the data fusion module. Read resourceaware data fusion algorithms for wireless sensor networks by ahmed abdelgawad available from rakuten kobo.
Scribd is the worlds largest social reading and publishing site. We are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including nobel prize winners and some of the worlds mostcited researchers. This book introduces resourceaware data fusion algorithms to gather and combine data from multiple sources e. In 15, a variable weightbased fuzzy data fusion algorithm is proposed.
Having thus found a solution for practical sensor networking, the next essential enabler to seek was a suitable power source for wireless sensor nodes. Because of limited power source, energy consumption has been considered as the most critical factor when designing sensor network protocols. A strategy for avoiding energy holes based on data fusion in. Sensor fusion is also known as multisensor data fusion and is a subset of information fusion. This paper discusses about wireless sensor network, its architecture, data aggregation or fusion related algorithms. In addition, the gating technique is also applied to solve the problem of msdft mobilesensor data fusion tracking for targets, i. Data fusion with desired reliability in wireless sensor. Pdf data fusion in wireless sensor networks biljana. In order to map the raw sensor readings onto physical reality, a model of that reality is required to complement the readings. Data fusion in wireless sensor networks ieee conference. A study on data fusion of wireless sensor networks security. Therefore, fusiondriven routing protocols for sensor networks cannot optimize over communication cost only.
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. Frery federal university of alagoas ufal wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. Activity recognition system based on multisensor data. One of the most important challenges of such networks is the distributed management of the huge amount of data produced by sensors in network to reduce data traffic in network and minimize the energy. An approach to implement data fusion techniques in wireless. With the number of nodes increasing, the total number of nodes grows exponentially, and there is a need to improve physical conditions. Wireless sensor networks wsns are mostly deployed in a remote working environment, since sensor nodes are small in size, costefficient, lowpower devices, and have limited battery power supply. May 16, 2017 recent advancements in sensor technology, wireless networks and consequently wireless sensor networks and the increase in their applications in different fields have led to their great importance.
In order to reduce the data processing load on bs and efficiently distinguish the authenticity of archived data, izadi et al. Data fusion techniques for auto calibration in wireless sensor networks maen takruri 1, subhash challa 2, ramah yunis 1 centre for realtime information networks crin university of technology, sydney, australia 2 nicta victoria research laboratory, australia email. The purpose of the network is to sense the environment and report what happens in the area it is deployed in. Directional controlled fusion in wireless sensor networks. On the other hand, serial data fusion imposes the utilization of routing algorithms. A smart sensor contains its own datasheet parameters in memory and has a standard interface for wired or wireless connections, such as zigbee or wifi. One of the most important challenges of such networks is the distributed management of the huge amount of data produced by sensors in network to reduce data traffic in network and. Developing a fusion application is challenging in general, for the fusion operation typically requires timecorrelation and synchronization of. Extending the network lifetime of wireless sensor networks. 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. Introduction to wireless sensor networks types and applications.
The journal is intended to present within a single forum all of the developments in the field of multisensor, multisource, multiprocess information fusion and thereby promote the synergism among. Wireless sensor networks have emerged as a new informationgathering paradigm based on the collaborative effort of a large number of sensing nodes. Recent advancements in sensor technology, wireless networks and consequently wireless sensor networks and the increase in their applications in different fields have led to their great importance. The paper provides a more detailed look at some existing data fusion and topology management algorithms. The metaphor that the sensornet is a database is problematic, however, because sensors do not exhaustively represent the data in the real world. Our aim is to provide a better understanding of the current research issues in this field. Abstractthe application prospect in the market with huge thing networking are buzzing the third wave of information technology, its one of the core technology on two wireless sensor networks with energy, storage capacity, computing power, communications bandwidth resource constraints of the salient characteristics of data fusion, implementation is the inevitable choice. A new data fusion algorithm for wireless sensor networks. 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.
Data fusion improves the coverage of wireless sensor networks. At present, the resolved strategies mainly focus on nonuniform node distribution and adjusting transmission power. This article introduces a timeselective strategy for enhancing temporal consistency of input data for multisensor data fusion for innetwork data. While innetwork data fusion can reduce data redundancy and hence curtail network load, the fusion process itself may introduce signi.
Research article secure data fusion in wireless multimedia. Systemlevel calibration for data fusion in wireless sensor. Data fusion in wireless sensor networks yun liu, qingan. An approach to implement data fusion techniques in. A data fusion method in wireless sensor networks ncbi. Systemlevel calibration for data fusion in wireless sensor networks rui tan, michigan state university, usa guoliang xing, michigan state university, usa zhaohui yuan, huadong jiao tong university, p.