In wireless sensor networks, resourceconstrained sensor nodes are spread over a potentially large area to measure environmental characteristics such as. Energyefficient routing schemes for wireless sensor networks. Wireless sensor networks for data acquisition and information fusion. Related issues study of wireless sensor network security. Pdf study of data fusion in wireless sensor network. With the promotion of the latest technologies and the new requirement of humanitarian, the wireless multisensor system is applied broadly. The data fusion at various levels should be synchronized in. Data fusion in wireless sensor networks using fuzzy systems. 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.
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. The key idea of the data fusion is to combine data from different. Impact of data fusion on realtime detection in sensor. Data fusion with desired reliability in wireless sensor. Pre and post processing of the measured data in such networks is crucial to the conservation of power and communication resources. Abstract wireless sensor networks consist of a large number sensor nodes that are deployed in some geographical area.
Adaptive decision fusion with a guidance sensor in. Alkaraki j, kamal e 2004 routing techniques in wireless sensor networks. Routing correlated data with fusion cost in wireless sensor networks hong luo, jun luo, yonghe liu, sajal k. Adaptive decision fusion with a guidance sensor in wireless sensor networks zhaohuayu,1 qiangling,1 andyiyu2.
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. Methods, models, and classifications nakamura, loureiro, frery 2 enabling robotic attitude sensing and autonomous navigation through inertial sensor technology david churchill 2010. In 1990, the united states used wireless sensor networks to carry out military. The purpose of the network is to sense the environment and report what happens in the area it is deployed in. Hence, the data fusion technique has to be considered in wsn application. 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. Pdf data fusion in wireless sensor networks biljana. However, with the continuous application of wireless sensor networks, it raises higher demands for information integrity and privacy, data fusion faces new challenges. Directional controlled fusion in wireless sensor networks. Pdf wireless sensor networks for data acquisition and.
Data fusion of wireless sensor network for prognosis and. Data fusion, which fuses the collected data before they are sent to the base station, is usually. Due to the limitations of some sensor nodes, especially the limited amount of energy, innetwork data processing, such as data fusion, is very important. Chief of among these are the distributed nature of computation and deployment coupled with communications bandwidth and energy constraints typical of many sensor networks. Data acquisition and fusion system based on wireless sensor. 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. Wireless sensor networks wsn have gained much attention recently. Sensor networks are gaining considerable attention nowadays. Data fusion in wireless sensor networks yun liu, qingan. The goal may be to extract information not readily apparent in an individual sensors data, improve the quality of information compared to that provided by any individual data, or improve the operation of the network by optimizing usage of its resources. The loss of battery or energy may lead to failure of the entire network 14. Decision fusion in a wireless sensor network with a large. Challenges in wireless sensor network wireless sensor network assure a wide variety of application and realize these application in real world.
The three fundamental ways of combining sensor data are the. However, such a high overhead is not acceptable in sensor networks based on embedded and wireless platforms. Generally, a large number of sensor nodes, capable of collecting data, processing and communicating. 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. Loureiro federal university of minas gerais ufmg and alejandro c. 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. Pdf a data fusion method in wireless sensor networks. Information fusion helps these systems to better unify data. The application of these methods, however, requires some care due to a number of issues that are particular to sensor networks.
Sensor fusion helps in building a more accurate world model in order for the robot to navigate and behave more successfully. Sensor fusionbased event detection in wireless sensor. Isbn 97839026523, pdf isbn 9789535158394, published 20090201. Introduction one of the primary applications of wireless sensor networks is the detection of phenomena of interest in the monitored environment, e. Energyefficient and reliable transmission of sensory information is a key problem in wireless sensor networks. Sensor fusion is combining of sensory data or data derived from disparate sources such that the resulting information has less uncertainty than would be possible when these sources were used individually. 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. Data aggregation has been put forward as a particu larly useful paradigm for wireless routing in sensor net works 11, 12. Recently, wireless sensor networks wsn community has witnessed an application focus shift. Security mechanism of transmission encryption of network is introduced to protect the security. A study on data fusion of wireless sensor networks. Efficient multisource data fusion for decentralized.
Section 6 justifies the need for energy efficient data fusion. Pdf systemlevel calibration for data fusion in wireless. The aim of this thesis is to develop data fusion strategies for wireless sensor networks wsn that remove temporal or spatial redundancies between sensor measurements in order to decrease the. Decision fusion, wireless sensor networks, distributed detection, kernelbased learning. Synchronization of multiple levels of data fusion in wireless. Wireless communications and mobile computing wirel. Data fusion in wireless sensor networks ieee conference. 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. Section 5 present existing data fusion techniques in wireless sensor networks. Pdf data acquisition is one of the most relevant aspects in telemonitoring systems. A new data fusion algorithm for wireless sensor networks. When the wireless sensors network is equipped with cognitive radio, which. Nakamura analysis, research and technological innovation center fucapi federal university of minas gerais ufmg antonio a.
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. Synchronization of multiple levels of data fusion in. Directional controlled fusion in wireless sensor networks ymin chen, yvictor leung. Distributed sensor fusion data fusion in sensor networks is defined as the set of algorithms, processes, and protocols that combine data from multiple sensors. Data fusion improves the coverage of wireless sensor networks. The term data aggregation has become popular in the wireless sensor network com munity as a synonym for information fusion kalpakis et al.
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. As data either raw or fused is propagated towards the sink, multiple levels of data fusion are likely. The wsn is modeled by a homogeneous poisson point process. 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. A data fusion method in wireless sensor networks ncbi. In 27, a surveillance system has both lowend passive infrared sensors and highquality.
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 based on node trust evaluation in wireless. A witnessbased approach for data fusion assurance in wireless sensor networks wenliang du,jingdeng, yunghsiang s. Although, monitoring was the initial application of wireless sensor networks, innetwork data processing and near realtime actuation capability have made wireless sensor networks suitable candidate for event detection and alarming applications as. Distributed signal processing and data fusion methods for. Special issue on distributed sensor networks sciencedirect. Data acquisition and fusion system based on wireless sensor dan qiu1, shuli gong2 abstract. The sensor nodes sns compute local decisions about the intruders presence and send them to the cluster heads chs. Data fusion in mobile wireless sensor networks muhammad arshad, member, iaeng, mohamad alsalem, farhan a. Wireless sensor networks wsns are resourceconstrained networks, especially when the energy is highly constrained. Systemlevel calibration for data fusion in wireless sensor networks. Data fusion in wireless sensor networks a statistical. Data fusion with desired reliability in wireless sensor networks abstract. Optimal fusion rule for distributed detection in clustered.
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. Many practical wireless sensor networks have multiple sensor modalities 26. A witnessbased approach for data fusion assurance in. 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. A new data fusion algorithm for wireless sensor networks inspired. 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. A case study conference paper pdf available august 2010 with 435 reads how we measure reads.
Data fusion in sensor networks is defined as the set of algorithms, processes, and protocols that combine data from multiple sensors. One the computational intelligence algorithms is fuzzy logic or fuzzy system algorithm. Abstractin wireless sensor networks, innetwork data fusion is needed for. Performance analysis of distributed estimation for data fusion. The term uncertainty reduction in this case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic vision.
Data fusion improves the coverage of wireless sensor. Han abstract wireless sensor networks place sensors into an area to collect data and send them back to a base station. 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. Saad, nasrullah armi, nidal kamel abstractduring the. Wireless sensor networks, distributed detection, decision fusion, signal attenuation model. Varshney abstractin wireless sensor networks, sensor nodes are spread randomly over the coverage area to collect information of interest. Data fusion of wireless sensor network for prognosis and diagnosis. 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. Wsns, hesitant fuzzy entropy, data fusion, energy consumption. 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. Need for energy efficient data fusion in wireless sensor. Wireless sensor networks wsns have been used in various domains such as military applications e.
In order to further promote the research on the technology of data acquisition. Many conventional methods in various sciences are not able to properly support a high volume of. Distributed fusion of sensor data in a constrained. The paper focuses on issues related to the integration of wireless sensor network security data, analyzes. 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. Technology is now available to aid in surveillance of the battlespace at a cost that makes it affordable for individual soldiers and small units to use.
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. Data fusion, target detection, coverage, performance limits, wireless sensor network 1. 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. Data fusion technology is widely used in data processing due to its characteristic of less transfer data. These information fusion functions combine the information framespackets from. 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. Low cost, easily deployed, micro airborne, ground, and littoral sensor networks are the key to providing the type of. Kernelbased learning of decision fusion in wireless. To avoid these above disadvantages, a trust evaluation model based on the autonomous behavior of sensor node is proposed in this paper. Leach uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion. Wireless sensor networks wsns consist of large number of constrained wireless sensor nodes for the purpose of data gathering. Abstractin wireless sensor networks, innetwork data fusion is needed for energyef.
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