scholarly journals Underground Operator Monitoring Platform Based on Ultra-Wide Band WSN

2018 ◽  
Vol 14 (10) ◽  
pp. 219 ◽  
Author(s):  
Weicai Xie ◽  
Xiaofeng Li ◽  
Xi Long
Keyword(s):  
Wide Band ◽  
Wireless Sensor ◽  
Ultra Wide Band ◽  
Font Size ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Research Findings ◽  
Property Losses ◽  
Positioning Algorithm ◽  
Monitoring Platform

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">This paper aims to accurately locate underground personnel in coal mines. For this purpose, an underground personnel positioning platform was established on the wireless sensor network (WSN). Specifically, the ultra-wide band (UWB) and the time difference of arrival (TDOA) positioning algorithm were introduced briefly, in view of the underground operation environment. Then, the underground operator monitoring platform was developed based on UWB-WSN and compared it with different positioning techniques through experiments. The results show that the proposed platform achieved a high positioning accuracy and satisfied the needs of real-time monitoring of underground personnel. The research findings shed new light on the mitigation of personnel and property losses in coal mine accidents.</span>

Ultra-Wide-Band Wireless Sensor Network for Transmission of Streaming Data

2018 ◽  
Vol 7 (1) ◽  
pp. 91-102
Author(s):  
Yu.V. Andreyev ◽  
◽  
L.V. Kuzmin ◽  
M.G. Popov ◽  
A.I. Ryshov ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wide Band ◽  
Streaming Data ◽  
Wireless Sensor ◽  
Ultra Wide Band

scholarly journals Location measurement of an object using radio networks for Industry 4.0 applications

2021 ◽  
Vol 264 ◽  
pp. 05060
Author(s):  
Alexander Fedotov ◽  
Vladimir Badenko ◽  
Vladimir Kuptsov ◽  
Sergei Ivanov ◽  
Igor Struchkov
Keyword(s):  
Industry 4.0 ◽  
Wide Band ◽  
Indoor Positioning ◽  
Radio Networks ◽  
Time Difference ◽  
Ultra Wide Band ◽  
Time Difference Of Arrival ◽  
Radio Technology ◽  
Uwb Radio ◽  
Location Measurement

Indoor positioning methods using radio networks are investigated. Time Difference of Arrival (TDOA) method is studied deeply, and the main problems are revealed. Application of ultra-wide band (UWB) radio technology to TDOA method is discussed, and limitations to UWB receiver and transmitter are revealed. These results are of great importance for the organization of unmanned moving devices management in the paradigm of fully autonomous Fabric of the Future in Industry 4.0.

scholarly journals Development and Application of a New Positioning Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 14 (10) ◽  
pp. 80
Author(s):  
Guohong Gao ◽  
Feng Wei ◽  
Jianping Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Measurement Error ◽  
Wireless Sensor ◽  
Time Of Arrival ◽  
Unknown Parameters ◽  
Positioning Method ◽  
Research Findings ◽  
Positioning Algorithm ◽  
Technical Basis

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">This paper aims to create a desirable positioning method for nodes in wireless sensor networks (WSNs). For this purpose, a source node positioning algorithm was developed based on time-of-arrival (TOA), in view of the nonlinear correlation between the measured values and unknown parameters in the observation equation of TOA source position. Several experiments were carried out to evaluate the performance of the proposed algorithm in terms of time measurement error, computing complexity, location error and Cramér–Rao lower bound (CRLB). The results show that the CRLB acquired by this algorithm can be used for WSN node positioning, provided that the independent zero mean Gauss measurement error is sufficiently small. The research findings lay a solid technical basis for optimal management, load balance, efficient routing, and automatic topology control of WSNs.</span>

scholarly journals Wireless Sensor Network Multi-Hop Positioning Algorithm Based on Continuous Regression

2016 ◽  
Vol 12 (10) ◽  
pp. 11
Author(s):  
Weimin Han ◽  
Shijun Li ◽  
Weidong Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Process Model ◽  
Euclidean Distance ◽  
Engineering Application ◽  
Wireless Sensor ◽  
Font Size ◽  
Hop Count ◽  
Simulation Results ◽  
Positioning Algorithm

<p style="margin: 0in 0in 10pt;"><span style="-ms-layout-grid-mode: line;"><span style="font-family: Times New Roman; font-size: small;">The traditional multi-hop positioning algorithm is easily affected by the network anisotropy, thus resulting in unstable positioning performance. The wireless sensor network multi-hop positioning algorithm based on continuous regression is put forwarded in the paper to address this problem. By utilizing the continuous regression model, the mapping relationship between the hop count and Euclidean distance is constructed so as to transform the positioning process model into regression prediction. Theoretical analysis and simulation results show that the improved algorithm improves the positioning accuracy, and avoids the influence of the network topology anisotropy on the performance of the algorithm. The algorithm requires little expenditure and few parameters so it can be adapted to wireless sensor networks with irregular nodes distribution, and can be of great engineering application value.</span></span></p>

scholarly journals A Novel Wireless Sensor Node Positioning Algorithm Based on Ant Colony Optimization Algorithm and Neural Network

2018 ◽  
Vol 14 (10) ◽  
pp. 40
Author(s):  
Beichen Chen
Keyword(s):  
Neural Network ◽  
Ant Colony Optimization ◽  
Cluster Structure ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Wireless Sensor Node ◽  
Ant Colony Optimization Algorithm ◽  
Positioning Accuracy ◽  
Bee Colony ◽  
Positioning Algorithm

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">This paper aims to enhance the positioning accuracy of wireless sensor network (WSN) nodes. For this purpose, a WSN node positioning algorithm was proposed based on artificial bee colony (ABC) algorithm and the neural network (NN). First, the parameters between three anchor nodes and the target node were measured. Then, the ABC and NN were introduced to simulate and predict the ranging error, and the weight was determined according to the results. In the proposed algorithm, the cluster structure was effectively combined with the NN model. The weight of backpropagation NN was optimized by the ant colony optimization (ACO) algorithm. Then, the ACO-optimized NN was used to fuse the data collected by WSN nodes. The simulation results show that the proposed algorithm can improve the positioning accuracy of WSN nodes and reduce the time of the search. The research findings shed new light on the positioning of WSN nodes.</span>

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