Indoor positioning based on Wi-Fi Fingerprint Technique using Fuzzy K-Nearest Neighbor

Torteeka, Peerapong; Xiu, Chundi

doi:10.1109/ibcast.2014.6778188

Cited by 43 publications

(18 citation statements)

References 14 publications

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“…Depending on the algorithm used, the precision and complexity of the approach vary. Some of the methods to carry out the geolocation using WiFi networks are: power vector, power triangulation, proximity heuristics [6], method of the k-nearest neighbors [16], [17], probabilistic methods [15], and location using RTT through ping messages [1].…”

Section: ) Methods Of the K-nearest Neighborsmentioning

confidence: 99%

A Proposal for a Technological Solution to Improve user Experience in a Shopping Center based on Indoor Geolocation Services

Andrade¹,

Quintero²,

Gamess³

et al. 2018

ijacsa

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For shopping centers, mobile devices and their associated technologies represent great business opportunities and a way to improve the user experience within their facilities. These types of constructions are usually quite large, multi-story, and with a significant number of shops, services, where the visitors may find themselves having difficulties to have a complete and up-to-date list of the stores, determine which stores and services are those that meet the characteristics or specifications they seek, know the location of the shops or how to reach them. This research studies and contemplates different technologies, tools, and approaches for the development of a technological solution for shopping centers that offers in its functionality a geolocation system in the interior spaces of the buildings. Our technological solution includes a mobile application for the Android operating system implemented by using the native development approach, and a web application for managing data, where the contents and settings of the mobile application will be obtained following the client/server model through a private API. It is worth to mention that the already mentioned system of geolocation in interiors is implemented using WiFi technology and the different Access Points installed in the shopping center, through which users can obtain their position, locate the stores or services of their interest, and receive indications on how to reach them.

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Section: ) Methods Of the K-nearest Neighborsmentioning

confidence: 99%

A Proposal for a Technological Solution to Improve user Experience in a Shopping Center based on Indoor Geolocation Services

Andrade¹,

Quintero²,

Gamess³

et al. 2018

ijacsa

View full text Add to dashboard Cite

show abstract

“…Diferentes metodologías que utilizan fingerprint se han usado ampliamente en trabajos pasados con señales de radiofrecuencia, principalmente utilizando WiFi (Zhuang et al, 2015;Al et al, 2017;Niu et al, 2015;Swangmuang and Krishnamurthy, 2008;Le et al, 2014;Zou et al, 2015;Zhao and Wang, 2017;Torteeka and Chundi, 2014;Le Dortz, N. and Gain, F. and Zetterberg, 2012). Esto debido en gran parte a que la tecnología WiFi se encuentra comúnmente en muchos lugares cerrados y edificios.…”

Section: Estado Del Arteunclassified

Sistema de posicionamiento en interiores utilizando señales de radio estaciones FM comerciales y Deep Learning

Roman

Márquez-Viloria

Velásquez

et al. 2020

Rev. iberoam. autom. inform. ind.

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<p>Para dar solución al problema de posicionamiento en interiores, muchos autores han propuesto el uso de diversas técnicas. Desde la simulación de un Sistema de Posicionamiento Global (GPS) a través de antenas Pseudolites, la construcción de campos magnéticos artificiales, el uso de diversos sensores como visión, ultrasonido, unidades de medida inercial, entre otros. Hasta el uso de transmisores y receptores en el rango de la Radio Frecuencia como los presentes en una oficina. Muchos de los sistemas anteriormente mencionados dependen para su correcto funcionamiento de una instalación y configuración de equipos en el lugar de posicionamiento, lo cual puede llevar en ocasiones a costosas implementaciones. Es por esto que para realizar este trabajo hemos propuesto una metodología de posicionamiento en interiores que no requiere de adecuaciones e instalaciones en el lugar de aplicación. La metodología propuesta hace uso de las radio estaciones FM existentes y utiliza algoritmos de Deep Learning como algoritmo de posicionamiento.</p>

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“…By exploiting the Spearman rank correlation of RSSI measurements from different APs, we proposed an improved Spearman-distance-based KNN [15] location method. In our proposed approach, the localization procedure includes the following three steps: Firstly, the offline RSSI fingerprint database is built; Secondly, collecting the position fingerprint of the object; Thirdly, calculating the Spearman distance according to Equation (7) and then select all the locations with minimum Spearman Distance; Finally, execute the original KNN approach according to all the locations with minimum Spearman Distance and obtain the final location estimation.…”

Section: B Spearman Rank Correlation Coefficientmentioning

confidence: 99%

An Improved K-Nearest-Neighbor Indoor Localization Method Based on Spearman Distance

Xie

Wang

Nallanathan

et al. 2016

IEEE Signal Process. Lett.

161

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Indoor positioning based on Wi-Fi Fingerprint Technique using Fuzzy K-Nearest Neighbor

Cited by 43 publications

References 14 publications

A Proposal for a Technological Solution to Improve user Experience in a Shopping Center based on Indoor Geolocation Services

A Proposal for a Technological Solution to Improve user Experience in a Shopping Center based on Indoor Geolocation Services

Sistema de posicionamiento en interiores utilizando señales de radio estaciones FM comerciales y Deep Learning

An Improved K-Nearest-Neighbor Indoor Localization Method Based on Spearman Distance

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