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 contribution | A deep learning and RSSI based approach for indoor positioning |
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Original language | Turkish |
Title of host publication | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1-4 |
Number of pages | 4 |
ISBN (Electronic) | 9781538615010 |
DOIs | |
Publication status | Published - 5 Jul 2018 |
Event | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey Duration: 2 May 2018 → 5 May 2018 |
Publication series
Name | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 |
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Conference
Conference | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 |
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Country/Territory | Turkey |
City | Izmir |
Period | 2/05/18 → 5/05/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.