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Relevant bibliographies by topics / Assembly Line, Wireless Sensor Network, Localization

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Journal articles

Academic literature on the topic 'Assembly Line, Wireless Sensor Network, Localization'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Assembly Line, Wireless Sensor Network, Localization"

1

Gogolák, László, Igor Fürstner, and Szilveszter Pletl. "Wireless sensor network based localization in industrial environments." Analecta Technica Szegedinensia 8, no. 1 (2014): 91–96. http://dx.doi.org/10.14232/analecta.2014.1.91-96.

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The use of wireless devices has greatly increased in the last decade, and it has been one of the most widely used medium of information transmission. Within the wireless devices the wireless sensor networks are the most contemporary and most commonly researched field. The work deals with the industrial use of wireless sensor networks and more precisely with monitoring and controlling industrial assembly lines. The focus of this study is localization by the use of wireless technology in the above mentioned environment. In the experiment wireless sensors are placed on the base elements of curren

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2

Gogolák, László, and Igor Fürstner. "Wireless Sensor Network Aided Assembly Line Monitoring According to Expectations of Industry 4.0." Applied Sciences 11, no. 1 (2020): 25. http://dx.doi.org/10.3390/app11010025.

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Striving for excellence during the assembling process through incorporating the expectations of Industry 4.0 requires complex information management on issues of overall system status, especially the physical characteristics and position of the parts being assembled, as well as the assembling units and tools. This research introduces both an overall customized assembling system supervision model, which is based on a modified four-layer control system hierarchy that suits the specific requirements of such systems and the developed wireless sensor network technology for assembling process manage

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3

Yan, Xiaoyong, Aiguo Song, Jimin Yu, and Zhong Yang. "Toward Collinearity-Avoidable Localization for Wireless Sensor Network." Journal of Sensors 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/908956.

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In accordance with the collinearity problem during computation caused by the beacon nodes used for location estimation which are close to be in the same line or same plane, two solutions are proposed in this paper: the geometric analytical localization algorithm based on positioning units and the localization algorithm based on the multivariate analysis method. The geometric analytical localization algorithm based on positioning units analyzes the topology quality of positioning units used to estimate location and provides quantitative criteria based on that; the localization algorithm based o

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4

Jiang, Pei, Xue Liang Pang, and Li Dong. "Survey on Mobile Target Localization in Wireless Sensor Networks." Applied Mechanics and Materials 738-739 (March 2015): 133–39. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.133.

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As a novel technology of information acquisition and processing, Wireless Sensor Network (WSN) has been widely used for complex large-scale localization tasks. With global distribution and sensing ability, wireless sensor network can provide valid optimal localization for mobile targets. According to the key problems of mobile target localization under wireless sensor network, this paper depicted current research status in both of line-of-sight and non-line-of-sight environments. Typical and representative algorithms are sorted and their ideas are evaluated. Finally, we discussed and anticipat

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5

Cheng, Long, Mingkun Xue, Ze Liu, and Yong Wang. "A Robust Tracking Algorithm Based on a Probability Data Association for a Wireless Sensor Network." Applied Sciences 10, no. 1 (2019): 6. http://dx.doi.org/10.3390/app10010006.

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As one of the core technologies of the Internet of Things, wireless sensor network technology is widely used in indoor localization systems. Considering that sensors can be deployed to non-line-of-sight (NLOS) environments to collect information, wireless sensor network technology is used to locate positions in complex NLOS environments to meet the growing positioning needs of people. In this paper, we propose a novel time of arrival (TOA)-based localization scheme. We regard the line-of-sight (LOS) environment and non-line-of-sight environment in wireless positioning as a Markov process with

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6

Zhang, Hanqing, and Haitao Li. "Node Localization Technology of Wireless Sensor Network Based on RSSI Algorithm." International Journal of Online Engineering (iJOE) 12, no. 10 (2016): 51. http://dx.doi.org/10.3991/ijoe.v12i10.6206.

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<p style="margin: 0in 0in 10pt;"><span style="-ms-layout-grid-mode: line;"><span style="font-family: Times New Roman; font-size: small;">Wireless sensor network, as one of the system compositions of the Internet of Things, is an important carrier of the efficient use of rural resources. An accurate localization algorithm is of great significance to the complete coverage of the farmland monitoring area and to ensure the connectivity of the whole network. This paper carries out an experiment based on the signal intensities of network nodes of wireless sensor in different farmla

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7

Fan, Jianhua, Tao Liang, Tongxiang Wang, and Jianwei Liu. "Identification and Localization of the Jammer in Wireless Sensor Networks." Computer Journal 62, no. 10 (2019): 1515–27. http://dx.doi.org/10.1093/comjnl/bxz055.

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Abstract Wireless sensor network can be easily attacked by jammers for its shared character and open access to the wireless channel. Jamming attack could produce a significant threat to the network by interrupting the normal transmission of nodes. To this end, several anti-jamming countermeasures have been proposed to improve the quality of service of the wireless sensor network. As an important building block for anti-jamming countermeasures, the estimation of jammer’s location could provide us a possible way to eliminate jammers artificially. However, existing localization algorithms mainly

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8

Hua, Jingyu, Yejia Yin, Weidang Lu, Yu Zhang, and Feng Li. "NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks." Sensors 18, no. 9 (2018): 2991. http://dx.doi.org/10.3390/s18092991.

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The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual an

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9

., R. Divya. "LOCALIZATION BASED RANGE MAP STITCHING IN WIRELESS SENSOR NETWORK UNDER NON-LINE-OF-SIGHT ENVIRONMENTS." International Journal of Research in Engineering and Technology 03, no. 05 (2014): 248–52. http://dx.doi.org/10.15623/ijret.2014.0305047.

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10

Li, Qiyue, Baoyu Chu, Zhong Wu, et al. "RMDS: Ranging and multidimensional scaling–based anchor-free localization in large-scale wireless sensor networks with coverage holes." International Journal of Distributed Sensor Networks 13, no. 8 (2017): 155014771772465. http://dx.doi.org/10.1177/1550147717724659.

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Sensor node localization is a crucial aspect of many location-related applications that utilize wireless sensor networks. Among the many studies in the literature, multidimensional scaling-based localization techniques have been proven to be efficient, obtaining high accuracy with lower information requirements. However, when applied to large-scale wireless sensor networks with coverage holes, which are common in many scenarios, such as underground mines, the transmission path can become deviated, degrading the localization performance of this type of connectivity-based technique. Furthermore,

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