Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion

Pescaru, Dan; Curiac, Daniel-Ioan

doi:10.3390/s140304211

Cited by 28 publications

(14 citation statements)

References 22 publications

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“…In order to locate miners, the WMSNs cameras deployed in underground tunnels should be aware of positions of themselves as well as positions of adjacent cameras which are referred to the geometrical parameters in this paper. In fact, several algorithms of localization and calibration can be applied to obtain the geometrical parameters automatically [ 22 , 23 , 24 , 25 , 26 ]. However, in our experiments, cameras are deployed manually and their geometrical parameters are measured also manually.…”

Section: Architecture Of Wmsns and Location Scene For Underground mentioning

confidence: 99%

The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

You

Yang

Han

2015

Sensors

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Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner’s lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner’s lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner’s lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner’s lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels.

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Section: Architecture Of Wmsns and Location Scene For Underground mentioning

confidence: 99%

The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

You

Yang

Han

2015

Sensors

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“…Microelectromechanical systems (MEMS) [7], Wi-Fi [8][9][10] or GSM [11] as GPS assist systems). Finally, there are attempts to use various other systems for the role of localization systems such as Bluetooth [12][13][14][15], Zigbee [16,17], Infrared [18], Vision systems [19][20][21] etc.. As you can see, most of the available systems are implemented in IPS, and their use outside closed spaces meets with many limitations, such as operating range (Bluetooth, Zigbee, Infrared), stability (MEMS) or required technical facilities (vision systems).…”

Section: Introductionmentioning

confidence: 99%

The Concept of Comprehensive Data Analysis from Ultra-Wideband Subsystem for Smart City Positioning Purposes

Grzechca¹,

Hanzel²,

Paszek³

2018

Preprint

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As a part of the proposed article, the authors presented comprehensive data analysis for movement data that comes from a positioning system based on ultra-wide band (UWB) technology. For purpose of this article, a test was carried out during which the car equipped with cruise control overcame the given path at a speed from 10 km/h to 60 km/h. The obtained motion models (information about position) have been filtered through a series of filters - from fundamentals filters with a variable window (median, moving average, Savitzky-Golay filter), through more complex ones like the Wiener or Kalman filter. As a result, the authors proposed a form of data analysis and filtration depending on the speed of the moving object. In addition, the maximum accuracy that can be obtained for a given traffic model was also determined. The whole research proves that it is possible to use a system based on UWB technology in positioning objects for urban applications - smart city, in industry 4.0 applications as well as for positioning autonomous vehicles in urban applications, such as well as on highways to maintain cohesion of convoys vehicles.

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“…According to whether some location-aware nodes called anchor nodes need to be deployed in the WSN, the WSN localization algorithms can be divided into two categories: anchor-based localization algorithms [4] and anchor-free localization algorithms [5]. Usually, the localization accuracy of the former is better than that of the latter, therefore anchor-based localization algorithms are often used in scenarios which need high localization accuracy.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Localization and Location Verification in WSNs

Chen

Dai

Kezhen

et al. 2015

Sensors

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Localization is one of the most important technologies in wireless sensor networks. A lightweight distributed node localization scheme is proposed by considering the limited computational capacity of WSNs. The proposed scheme introduces the virtual force model to determine the location by incremental refinement. Aiming at solving the drifting problem and malicious anchor problem, a location verification algorithm based on the virtual force mode is presented. In addition, an anchor promotion algorithm using the localization reliability model is proposed to re-locate the drifted nodes. Extended simulation experiments indicate that the localization algorithm has relatively high precision and the location verification algorithm has relatively high accuracy. The communication overhead of these algorithms is relative low, and the whole set of reliable localization methods is practical as well as comprehensive.

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Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion

Cited by 28 publications

References 22 publications

The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

The Concept of Comprehensive Data Analysis from Ultra-Wideband Subsystem for Smart City Positioning Purposes

Collaborative Localization and Location Verification in WSNs

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