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

Translated title of the contribution: A deep learning and RSSI based approach for indoor positioning

Kamuran Doǧuş Yüksel, Behçet Ugür Töreyin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

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.

Translated title of the contributionA deep learning and RSSI based approach for indoor positioning
Original languageTurkish
Title of host publication26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781538615010
DOIs
Publication statusPublished - 5 Jul 2018
Event26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey
Duration: 2 May 20185 May 2018

Publication series

Name26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Conference

Conference26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Country/TerritoryTurkey
CityIzmir
Period2/05/185/05/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

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