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Paper Abstract and Keywords
Presentation 2024-08-27 14:15
2-Step Robust DNN Model for RSSI-based Indoor Localization
Taisei Kosaka (Yokohama National Univ.), Steven Wandale (Univ. of Malawi), Koichi Ichige (Yokohama National Univ.) SIP2024-60
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we introduce a novel approach called the 2-Step Robust Deep Neural Network (DNN), designed specifically for indoor localization utilizing received signal strength indicator (RSSI) data.
The conventional method, 2-Step Extreme Gradient Boosting (XGBoost), improves estimation accuracy by utilizing one of the two-dimensional coordinates ($x$ or $y$ coordinate) as an input feature. However, it has limitations in estimation accuracy for complex and nonlinear datasets, and its performance deteriorates when the input positional coordinates deviate from the ground truth during testing.
The 2-Step Robust DNN proposed in this paper incorporates two enhancements over the 2-Step XGBoost.
Through comprehensive simulations, we demonstrate that the proposed 2-Step Robust DNN attains superior estimation accuracy while preserving the absence of constraints on the dataset.
Keyword (in Japanese) (See Japanese page) 
(in English) Indoor localization / DNN / RSSI / / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 162, SIP2024-60, pp. 75-80, Aug. 2024.
Paper # SIP2024-60 
Date of Issue 2024-08-19 (SIP) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SIP2024-60

Conference Information
Committee SIP  
Conference Date 2024-08-26 - 2024-08-27 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Fukui (Bunkyo Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Signal processing, etc. 
Paper Information
Registration To SIP 
Conference Code 2024-08-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) 2-Step Robust DNN Model for RSSI-based Indoor Localization 
Sub Title (in English)  
Keyword(1) Indoor localization  
Keyword(2) DNN  
Keyword(3) RSSI  
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1st Author's Name Taisei Kosaka  
1st Author's Affiliation Yokohama National University (Yokohama National Univ.)
2nd Author's Name Steven Wandale  
2nd Author's Affiliation University of Malawi (Univ. of Malawi)
3rd Author's Name Koichi Ichige  
3rd Author's Affiliation Yokohama National University (Yokohama National Univ.)
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Speaker Author-1 
Date Time 2024-08-27 14:15:00 
Presentation Time 20 minutes 
Registration for SIP 
Paper # SIP2024-60 
Volume (vol) vol.124 
Number (no) no.162 
Page pp.75-80 
#Pages
Date of Issue 2024-08-19 (SIP) 


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