A multi-step approach for RSSi-based distance estimation using smartphones

Chowdhury, Tanney; Rahman, Mostafizur; Parvez, Sadre-Ala; Basher, A.M. Hasanul; Alam, A. K. M. M.; Rizwan, Shahriar

doi:10.1109/nsyss.2015.7042942

Cited by 44 publications

(28 citation statements)

References 4 publications

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“…El RSSI no se encuentra estandarizado; la escala de valores depende tanto del emisor como del receptor, es decir, dos receptores diferentes tendrán una escala diferente, aunque se trate del mismo emisor (Chowdhury et al, 2015).…”

Section: Experimentaciónunclassified

Posicionamiento en espacios interiores con Android, Bluetooth y RSSI

Cabrera-Goyes

Camacho

2018

Enfoque UTE

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La investigación presentada tuvo dos objetivos. En primer lugar determinar de manera experimental la relación existente entre RSSI y distancia. En segundo lugar, mediante el uso de técnicas de trilateración, establecer la posición del receptor dentro del entorno en el cual se efectuó la experimentación. Las contribuciones principales son: determinar cómo los dispositivos Bluetooth interactúan entre ellos y las diferencias existentes al utilizar mediciones RSSI; recopilar data en distancias controladas y someter esta información a análisis de regresión para establecer la relación entre RSSI y distancia; evaluar técnicas de trilateración de base para generar un prototipo funcional de posicionamiento en interiores con dispositivos Android. Los resultados son alentadores puesto que, inclusive con una configuración sumamente heterogénea de hardware y software y sin emplear ningún tipo de dispositivo especializado, fue posible obtener una alta precisión promedio.

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Section: Experimentaciónunclassified

Posicionamiento en espacios interiores con Android, Bluetooth y RSSI

Cabrera-Goyes

Camacho

2018

Enfoque UTE

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“…Their main goal has been to enhance the mean positioning error and accuracy of Wi-Fibased indoor localization mechanisms. In [24], the authors have shown that the use of particles filters or Kalman filter algorithms may not always be a good choice for BLE4.0 beacon, where the use of different classification algorithms seems to provide better results. From the above, it is clear that the development of accurate and robust wireless indoor localization mechanisms is still a long way to go.…”

Section: Standard Wirelessmentioning

confidence: 99%

“…All the parameters in (1) can be experimentally measured except , which needs to be estimated. Classical approaches determine the value that minimizes the estimation error in a set of ground truth preliminary measurements [24]. This is usually done using the lowest squared error as metric.…”

Section: Radiopropagation Modelmentioning

confidence: 99%

An Analysis of Multiple Criteria and Setups for Bluetooth Smartphone-Based Indoor Localization Mechanism

et al. 2017

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Bluetooth Low Energy (BLE) 4.0 beacons will play a major role in the deployment of energy-efficient indoor localization mechanisms. Since BLE4.0 is highly sensitive to fast fading impairments, numerous ongoing studies are currently exploring the use of supervised learning algorithm as an alternative approach to exploit the information provided by the indoor radio maps. Despite the large number of results reported in the literature, there are still many open issues on the performance evaluation of such approach. In this paper, we start by identifying, in a simple setup, the main system parameters to be taken into account on the design of BLE4.0 beacons-based indoor localization mechanisms. In order to shed some light on the evaluation process using supervised learning algorithm, we carry out an in-depth experimental evaluation in terms of the mean localization error, local prediction accuracy, and global prediction accuracy. Based on our results, we argue that, in order to fully assess the capabilities of supervised learning algorithms, it is necessary to include all the three metrics.

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“…To solve this problem, existing research (1)(2)(3)(4)(5)(6)(7)(8)(9) has proposed a navigation system that leads visually impaired people on the route to their destination by detecting obstacles on the route and tracking their position using information and communication technology.…”

Section: Introductionmentioning

confidence: 99%

“…(3) GPS can measure a person's position outdoors with an error of 0.5 m. WiFi positioning and BLE positioning can measure a person's position indoors with error between 1 and 10 m. Visually impaired people recognize their position and the route to their destination by combining these positioning methods. On the other hand, existing studies (4)(5)(6)(7)(8)(9) have been able to detect obstacles such as a bumpy road and a flight of stairs.…”

Section: Introductionmentioning

confidence: 99%

High-Speed Detection of Down Staircase for Visually Impaired People Using Illuminance of Point Pattern

2016

Sensors and Materials

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Keywords: phase only correlation, Hough transform, illuminance of point pattern, detection of down staircaseVisually impaired people are limited in movement both indoors and outdoors. To solve this problem, existing studies propose a navigation system that leads visually impaired people on the route to their destination by detecting obstacles on the route and tracking their position using information and communication technology. Visually impaired people recognize their position and the route to their destination by combining these positioning methods. On other hand, existing studies propose detection of obstacles by image processing, but this method take a long time. Hence, we have proposed the high-speed detection of a down staircase for visually impaired people. The proposed method quickly detects the boundary line between the down staircase and floors using the illuminance of a point pattern. Moreover, the proposed method recognizes the down staircase quickly because it removes images that are clearly different from the down staircase and applies image processing to the pedestrian route only. Experimental results have shown that the proposed method can recognize a down staircase and border line with more than 90% accuracy. As a result, visually impaired people can safely go down a flight of stairs using this method.

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A multi-step approach for RSSi-based distance estimation using smartphones

Cited by 44 publications

References 4 publications

Posicionamiento en espacios interiores con Android, Bluetooth y RSSI

Posicionamiento en espacios interiores con Android, Bluetooth y RSSI

An Analysis of Multiple Criteria and Setups for Bluetooth Smartphone-Based Indoor Localization Mechanism

High-Speed Detection of Down Staircase for Visually Impaired People Using Illuminance of Point Pattern

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