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

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

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"

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Gogolák, László, Igor Fürstner, and Szilveszter Pletl. "Wireless sensor network based localization in industrial environments." Analecta Technica Szegedinensia 8, no. 1 (January 11, 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 currently being assembled products. The developed system is able to specify the precise place of the product in the assembly line and record the time of localization. By the use these information the time of assembling the product can be monitored. For determining the place of the product the Received signal strength indication – RSSI has been used. The current position of the product is calculated by a neural network. The use of these sensors makes possible the measuring and recording of the influences on the product during the assembly, such as the effects of temperature, humidity, or if the product has been hit or damaged. By the use of these wireless sensor networks the quality of the assembled products can be improved and the process of assembly can be optimized.
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Gogolák, László, and Igor Fürstner. "Wireless Sensor Network Aided Assembly Line Monitoring According to Expectations of Industry 4.0." Applied Sciences 11, no. 1 (December 22, 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 management with a particular focus on localization. The developed model highlights the localization problems of the system as well as other aspects required for overall system status determination. The localization of assembled parts is based on the fingerprint localization method by using the received signal strength indicator. The proposed localization algorithms are based either on artificial neural networks or on the weighted k-nearest neighbor method. The developed model has been tested both in laboratory conditions and in a simulated industrial environment. The research results offer a general solution to the problem of assembling system supervision, regardless of size and shape, with emphasis on the localization problem solution.
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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 on the multivariate analysis method uses the multivariate analysis method to filter and integrate the beacon nodes coordinate matrixes during the process of location estimation. Both methods can avoid low estimation accuracy and instability caused by multicollinearity.
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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 anticipated the future research direction.
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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 (December 18, 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 two interactive models. In the NLOS model, we propose a modified probabilistic data association (MPDA) algorithm to reduce the NLOS errors in position estimation. After the NLOS recognition, if the number of correct positions is zero continuously, it will lead to inaccurate localization. In this paper, the NLOS tracer method is proposed to solve this problem to improve the robustness of the probabilistic data association algorithm. The simulation and experimental results show that the proposed algorithm can mitigate the influence of NLOS errors and achieve a higher localization accuracy when compared with the existing methods.
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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 (October 31, 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 farmland environments having crops or not at different placing heights and relative distances. In the research, an analysis is made on the attenuation relationship between the RSSI values and the distance and height between nodes. Besides, multiple linear regression methods are used to fit the propagation model of wireless signal. Then, a distance-measuring experiment is carried out according to the model, and finally the localization of unknown nodes is realized based on Gauss mixed algorithm. Average error of the experiment is 1.02m, indicating good experimental results.</span></span></p>
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Fan, Jianhua, Tao Liang, Tongxiang Wang, and Jianwei Liu. "Identification and Localization of the Jammer in Wireless Sensor Networks." Computer Journal 62, no. 10 (July 3, 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 pay attention to locate the jammers that are equipped with omnidirectional antennas, which usually fail to cope with directional jammers. In order to bridge this gap, an algorithm of antenna identification and localization of the jammer (AILJ) based on the topology information of jamming scenarios is put forward in this paper. At first, a collection protocol is designed to collect the information of boundary nodes and jammed nodes. Then, an identification method based on the classification of the boundary nodes is proposed to derive the type of jammer’s antenna. At last, a range-free method is put forward to locate the jammer without relying on the propagation parameters. The proposed AILJ only depends on the localization of jammed nodes and boundary nodes and employs their geometry knowledge. For the omnidirectional jammer, the mean center of two circumcircles is considered as the jammer’s position. For the directional jammer, the mean value of the intersections between the straight line that represents jammer’s direction and the circumcircles is considered as the directional jammer’s position. Finally, a series of experiments have been conducted to evaluate the identification and localization performance of AILJ.
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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 (September 7, 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 analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.
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., 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 (May 25, 2014): 248–52. http://dx.doi.org/10.15623/ijret.2014.0305047.

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Li, Qiyue, Baoyu Chu, Zhong Wu, Wei Sun, Liangfeng Chen, Jie Li, and Zhi Liu. "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 (August 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, in such complex wireless environments, non-line-of-sight reference objects, the presence of obstacles and signal fluctuations change the communication range and make it difficult to obtain an accurate position. In this article, we present a anchor-free localization scheme for large-scale wireless sensor networks called the ranging and multidimensional scaling–based localization scheme. We use ranging and non-line-of-sight error mitigation techniques to estimate accurate distances between each node pair and attempt to find inflection nodes using a novel flooding protocol to correct transmission paths that have become deviated by a coverage hole. Moreover, we replace the singular value decomposition with an iterative maximum gradient descent method to reduce the computational complexity. The results of the simulations and experiments show that our scheme performs well on wireless sensor networks with different coverage holes and is robust to varying network densities.
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Dissertations / Theses on the topic "Assembly Line, Wireless Sensor Network, Localization"

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Laslo, Gogolak. "Uticaj bežične senzorske tehnologije na upravljanje montažnim sistemima." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2014. http://www.cris.uns.ac.rs/record.jsf?recordId=85806&source=NDLTD&language=en.

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U doktorskoj disertaciji obrađen je problem upravljanja montažnimsistemima pomoću bežične senzorske tehnologije u cilju poboljšanjaefikasnosti proizvodnje i poboljšanja kvaliteta proizvoda. U okviruove disertacije je razvijen model bežičnog upravljačkog sistema zaupravljanje i nadzor industrijskih procesa. Glavni cilj istraživanjaje razvoj integrisanog sistema za praćenje pozicije radnog predmeta ipraćenje okolnosti u kojima se radni predmet nalazi u montažnimsistemima. Rezultati istraživanja su potvrđeni eksperimentalnimistraživanjem u laboratorijskoj i u realnoj industrijskoj sredini.
The dissertation deals with the problem of monitoring and controllingindustrial assembly lines by wireless sensor technology with the aim ofimproving the efficiency of production and the quality of the product. A modelof a wireless controlling system has been developed for monitoring andcontrolling industrial processes. The main focus of the study is thedevelopment of an integrated system for monitoring the position of theproduct and the influences on the product in the assembly lines. The resultsare confirmed by experiments in a laboratory and real industrial environment.
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Ngo, Tan A. "Wireless source localization and signal collection from an airborne symmetric line array sensor network." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43965.

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Approved for public release; distribution is unlimited
Wireless communication technology has become a critical aspect in many civilian and military applications. With regard to remote sensing, search and rescue, disaster relief operations and signals intelligence, there exists an interest in developing capabilities to collect these signals-of-interest. The objective of this dissertation is to maximize signal collection performance in the presence of signal measurement and sensor related errors. To accomplish this objective, we proposed a signal collection scheme that exploits an elevated, mobile network to maximize the collaborative collection of a target signal. The proposed scheme begins with source localization. This technique consists of an initial weighted least-squares estimate followed by a maximum-likelihood estimate. Implemented on an elevated, mobile network, this technique is able to obtain an optimal localization. To enhance localization robustness, we developed an outlier rejection process that mitigates the effects of measurement and sensor position errors. To collect the signal, this research quantified the effects of sensor position errors on beamforming and proposed a novel signal collection scheme that combines signal estimation and collaborative beamforming. Using all these techniques in concert, we were able to show that the proposed scheme outperforms standard collaborative beamforming in the presence of sensor position errors.
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Book chapters on the topic "Assembly Line, Wireless Sensor Network, Localization"

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McGuire, Michael L., and Konstantinos N. Plataniotis. "Accuracy Bounds for Wireless Localization Methods." In Localization Algorithms and Strategies for Wireless Sensor Networks, 380–405. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-396-8.ch015.

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Node localization is an important issue for wireless sensor networks to provide context for collected sensory data. Sensor network designers need to determine if the desired level of localization accuracy is achievable from their network configuration and available measurements. The Cramér-Rao lower bound is used extensively for this purpose. This bound is loose since it uses only information from measurements in its calculations. Information, such as that from the sensor selection process, is not considered. In addition, non-line-of-sight radio propagation causes the regularity conditions of the Cramér-Rao lower bound to be violated. This chapter demonstrates the Weinstein-Weiss and extended Ziv-Zakai lower bounds for localization error which remain valid with non-line-of-sight propagation. These bounds also use all available information for bound calculations. It is demonstrated that these bounds are tight to actual estimator performance and may be used determine the available accuracy of location estimation from survey data collected in the network area.
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EL-Darieby, Mohamed, Hazem Ahmed, Mahmoud Halfawy, Ahmed Amer, and Baher Abdulhai. "A Wireless Mesh Network Platform for Vehicle Positioning and Location Tracking." In Localization Algorithms and Strategies for Wireless Sensor Networks, 430–45. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-396-8.ch017.

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Large urban areas in North America as well as many other parts of the world are experiencing unprecedented and soaring congestion problems. It is imperative that modern societies upgrade their transportation systems in order to remain competitive, and maintain the high quality of life and social wellbeing. Current practices in Intelligent Transportation Systems (ITS) data gathering are dominated by the use of point detectors for surveillance, and wire-line communication networks for data transmission. Reliance on point detectors is losing appeal due to detector reliability issues, the cost of building and maintaining detector networks, and potential traffic disruption during construction and maintenance of these networks. This chapter describes a novel wireless mesh network platform for traffic monitoring. The platform uses traveling cars as data collection probes and uses wireless municipal mesh networks to transport sensed data. The platform assumes that cars or drivers’ mobile devices are equipped with the widely adopted low-cost Bluetooth wireless technology. Field trials of the proposed platform demonstrated its capability to track cars traveling at speeds of 0 to 70 km/hour. The platform was able to track cars as they travel and turn on a typical road network. In addition, the platform was used to approximate car speeds through determining the change in position in a time period. The preliminary results indicated an accuracy of ± 10%- 15%. The chapter describes the architecture, implementation, and field-testing of the proposed platform. It also discusses aspects of large-scale deployment of the proposed platform to cover large geographic areas.
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Miloud, Mihoubi, Rahmoun Abdellatif, and Pascal Lorenz. "A Novel Bat Algorithm for Line-of-Sight Localization in Internet of Things and Wireless Sensor Network." In Machine Learning and Cognitive Science Applications in Cyber Security, 213–39. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8100-0.ch009.

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WSNs have recently been extensively investigated due to their numerous applications where processes have to be spread over a large area. One of the important challenges in WSNs is secure node localization. Its main objective is to protect the circulated information in WSN for any attack with low energy. For this reason, recent approaches relying on swarm intelligence techniques are called and the node localization is seen as an optimization problem in a multi-dimensional space. In this chapter, the authors present an improvement to the original bat algorithm for information protecting during the localization task. Hence, the proposed approach computes iteratively the position of the nodes and studied the scalability of the algorithm on a large WSN with hundreds of sensors that shows pretty good performance. Moreover, the parameters are simulated in different scenarios of simulation. In addition, a comparative study is conducted to give more performance to the proposed algorithm.
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Conference papers on the topic "Assembly Line, Wireless Sensor Network, Localization"

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Fan, Zhibo, Hao Chu, Fei Wang, and Jian Lu. "A New Non-Line-of-Sight Localization Algorithm for Wireless Sensor Network." In 2020 IEEE 6th International Conference on Computer and Communications (ICCC). IEEE, 2020. http://dx.doi.org/10.1109/iccc51575.2020.9344936.

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Cheng, Long, Siyu Li, and Yuchao Shao. "A non-line of sight identification based localization method for wireless sensor network." In 2017 IEEE 9th International Conference on Communication Software and Networks (ICCSN). IEEE, 2017. http://dx.doi.org/10.1109/iccsn.2017.8230127.

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