Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim

Kamuran Doǧuş Yüksel; Behçet Ugür Töreyin

doi:10.1109/SIU.2018.8404614

Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim

Kamuran Doǧuş Yüksel
, Behçet Ugür Töreyin

Bilişim Enstitüsü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

3 Atıf (Scopus)

Özet

Indoor positioning and navigation systems are getting popular nowadays. There are different types of products in the way of accuracy, cost and power consumption in the field. Especially in the last couple of years, RSSI (Received Signal Strength Indicator) based positioning algorithms have studied but the results are not sufficient and there is no exact way decided to overcome this problem. In this paper, we will explain a method that combines Deep Learning and BLE (Bluetooth Low Energy) Fingerprinting method to get better accurate results.

Tercüme edilen katkı başlığı	A deep learning and RSSI based approach for indoor positioning
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1-4
Sayfa sayısı	4
ISBN (Elektronik)	9781538615010
DOI'lar	https://doi.org/10.1109/SIU.2018.8404614
Yayın durumu	Yayınlandı - 5 Tem 2018
Etkinlik	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey Süre: 2 May 2018 → 5 May 2018

Yayın serisi

Adı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Ülke/Bölge	Turkey
Şehir	Izmir
Periyot	2/05/18 → 5/05/18

Bibliyografik not

Publisher Copyright:
© 2018 IEEE.

Keywords

Artificial Neural Network
BLE
Deep Learninng
Fingerprinting
Indoor Positioning

Belgeye Erişim

10.1109/SIU.2018.8404614

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Yüksel, K. D., & Töreyin, B. U. (2018). Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 (pp. 1-4). (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2018.8404614

Yüksel, Kamuran Doǧuş ; Töreyin, Behçet Ugür. / Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

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title = "Kapali alan konumlandirma i{\c c}in derin oǧrenme ve sinyal gucu indikatoru tabanli bir yakla{\c s}im",

abstract = "Indoor positioning and navigation systems are getting popular nowadays. There are different types of products in the way of accuracy, cost and power consumption in the field. Especially in the last couple of years, RSSI (Received Signal Strength Indicator) based positioning algorithms have studied but the results are not sufficient and there is no exact way decided to overcome this problem. In this paper, we will explain a method that combines Deep Learning and BLE (Bluetooth Low Energy) Fingerprinting method to get better accurate results.",

keywords = "Artificial Neural Network, BLE, Deep Learninng, Fingerprinting, Indoor Positioning",

author = "Y{\"u}ksel, \{Kamuran Doǧu{\c s}\} and T{\"o}reyin, \{Beh{\c c}et Ug{\"u}r\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 ; Conference date: 02-05-2018 Through 05-05-2018",

year = "2018",

month = jul,

day = "5",

doi = "10.1109/SIU.2018.8404614",

language = "T{\"u}rk{\c c}e",

series = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--4",

booktitle = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

address = "United States",

}

Yüksel, KD & Töreyin, BU 2018, Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim. in 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Izmir, Turkey, 2/05/18. https://doi.org/10.1109/SIU.2018.8404614

Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim. / Yüksel, Kamuran Doǧuş; Töreyin, Behçet Ugür.
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim

AU - Yüksel, Kamuran Doǧuş

AU - Töreyin, Behçet Ugür

PY - 2018/7/5

Y1 - 2018/7/5

N2 - Indoor positioning and navigation systems are getting popular nowadays. There are different types of products in the way of accuracy, cost and power consumption in the field. Especially in the last couple of years, RSSI (Received Signal Strength Indicator) based positioning algorithms have studied but the results are not sufficient and there is no exact way decided to overcome this problem. In this paper, we will explain a method that combines Deep Learning and BLE (Bluetooth Low Energy) Fingerprinting method to get better accurate results.

AB - Indoor positioning and navigation systems are getting popular nowadays. There are different types of products in the way of accuracy, cost and power consumption in the field. Especially in the last couple of years, RSSI (Received Signal Strength Indicator) based positioning algorithms have studied but the results are not sufficient and there is no exact way decided to overcome this problem. In this paper, we will explain a method that combines Deep Learning and BLE (Bluetooth Low Energy) Fingerprinting method to get better accurate results.

KW - Artificial Neural Network

KW - BLE

KW - Deep Learninng

KW - Fingerprinting

KW - Indoor Positioning

UR - https://www.scopus.com/pages/publications/85050795743

U2 - 10.1109/SIU.2018.8404614

DO - 10.1109/SIU.2018.8404614

M3 - Konferans katkısı

AN - SCOPUS:85050795743

T3 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

SP - 1

EP - 4

BT - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Y2 - 2 May 2018 through 5 May 2018

ER -

Yüksel KD, Töreyin BU. Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4. (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). doi: 10.1109/SIU.2018.8404614

Kapali alan konumlandirma için derin oǧrenme ve sinyal gucu indikatoru tabanli bir yaklaşim

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap