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JCR Impact Factor: 0.699
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Issues per year: 4
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Next issue: May 2019
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  4/2018 - 10

Indoor Localization using Voronoi Tessellation

ARIF, M. See more information about ARIF, M. on SCOPUS See more information about ARIF, M. on IEEExplore See more information about ARIF, M. on Web of Science, WYNE, S. See more information about  WYNE, S. on SCOPUS See more information about  WYNE, S. on SCOPUS See more information about WYNE, S. on Web of Science, JUNAID NAWAZ, A. See more information about JUNAID NAWAZ, A. on SCOPUS See more information about JUNAID NAWAZ, A. on SCOPUS See more information about JUNAID NAWAZ, A. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,387 KB) | Citation | Downloads: 121 | Views: 223

Author keywords
indoor environments, interpolation, radio propagation, simultaneous localization and mapping, wireless LAN

References keywords
systems(10), location(9), indoor(9), localization(7), positioning(6), services(5), voronoi(4), information(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 85 - 90
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04010
Web of Science Accession Number: 000451843400010
SCOPUS ID: 85058775391

Abstract
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Recently the use of received signal strength values from a wireless local area network has received significant research interest for indoor localization. This work investigates a Voronoi-based interpolation method to improve indoor localization performance. The region of interest is spanned by reference measurement locations, termed as anchors. The proposed method is shown to outperform well-known localization techniques such as the k-Nearest Neighbor (k-NN) and the Inverse Distance Weighting (IDW) methods in terms of accuracy and precision. Our results show that for a 20 m x 20 m room the proposed scheme can achieve a location accuracy of 5.7 m with at most 5 anchors, whereas the IDW and k-NN techniques attain location accuracies of only 6.1 m and 6.5 m, respectively, under the same conditions. These performance gains are achieved while maintaining the same number of anchors in the system calibration phase for all the considered techniques.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 4]


[2] R. Zekavat and R. M. Buehrer, "Handbook of position Location: Theory, Practice and Advances", IEEE Series on Digital and Mobile Communication, Wiley-IEEE Press, 2011.

[3] A. Yassin, Y. Nasser, M. Awad, A. Al-Dubai, R. Liu, C. Yuen, R. Raulefs and E. Aboutanios, "Recent advances in indoor localization: A survey on theoretical approaches and applications," IEEE Communications Surveys & Tutorials. Vol. 19, no. 2, pp. 1327-1346, 2016.
[CrossRef] [Web of Science Times Cited 61]


[4] W. Zhao, S. Han, W. Meng, and D. Zou, "A testbed of performance evaluation for fingerprint based WLAN positioning system," KSII transaction on internet and information systems, vol. 10, no. 6, pp. 2583-2605, 2016.
[CrossRef] [Web of Science Times Cited 4]


[5] D. Han, S. Jung, M. Lee, and G. Yoon, "Building a practical Wi-Fi-based indoor navigation system," IEEE Pervasive Computing, vol. 13, no. 2, pp. 72-79, 2014.
[CrossRef]


[6] Y. Mo, Z. Zhang, Y. Lu, and G. Agha, "A novel technique for human traffic based radio map updating in Wi-Fi indoor positioning systems," KSII Transactions on Internet and Information Systems, vol. 9, no. 5, pp. 1881-1903, 2015.
[CrossRef] [Web of Science Times Cited 4]


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[CrossRef]


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[CrossRef]


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[CrossRef]


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[CrossRef]


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[CrossRef]


[12] P. Mirowski, P. Whiting, H. Steck, R. Palaniappan; et al., "Probability kernel regression for Wi-Fi localization," Journal of Location based Services, vol. 6, no. 2, pp. 81-100, 2012.
[CrossRef]


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[CrossRef]


[14] V. C. Gungor and M. K. Korkmaz, "Wireless link-quality estimation in smart grid environments," International Journal of Distributed Sensor Networks, vol. 8, no. 2, 2012.
[CrossRef] [Web of Science Times Cited 10]


[15] D. Wu, Y. Xu, and L. Ma, "Research on RSS based Indoor Location Method," in Proc. IEEE Pacific-Asia Conf. on Knowledge Engineering and Software Engineering, Jan. 2010, pp. 205-208.
[CrossRef] [Web of Science Times Cited 7]


[16] N. Hernandez, A. Hussein, D. Cruzado, I. Parra, and J. M. Armingol. "Applying low cost WiFi-based localization to in-campus autonomous vehicles," in Proc. 20th IEEE International Conference on Intelligent Transportation Systems (ITSC), 2017, pp. 1-6.
[CrossRef]


[17] M. R. K. Aziz, L. Yuto and T. Matsumoto, "A New RSS-based Wireless Geolocation Technique Utilizing Joint Voronoi and Factor Graph," International Journal of Simulation: Systems, Science and Technology, 2016.
[CrossRef]


[18] F. Shang, Y. Jiang, A. Xiong, W. Su and L. He. "A Node Localization Algorithm Based on Multi-Granularity Regional Division and the Lagrange Multiplier Method in Wireless Sensor Networks," Sensors, vol. 16, no. 11, 2016.
[CrossRef] [Web of Science Times Cited 2]


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[CrossRef] [Web of Science Times Cited 32]


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[CrossRef]


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[CrossRef] [Web of Science Times Cited 37]


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[23] Z. Xiong, F. Sottile, M. A. Spirito and R. Garello, "Hybrid Indoor Positioning Approaches Based on WSN and RFID," in Proc. 4th IFIP International Conference on New Technologies, Mobility and Security, 2011, pp. 1-5.
[CrossRef]


[24] Y. Seidel and T. S. Rappaport, "914 MHz path loss prediction model for indoor wireless communication in multi-floored buildings," IEEE Transactions on Antennas and Propagation, vol. 40, no. 2, pp. 201-217, 1992.
[CrossRef] [Web of Science Times Cited 404]




References Weight

Web of Science® Citations for all references: 565 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 23 ACR
SCOPUS® Average Citations per reference: 0

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-03-19 01:19 in 152 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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