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Paper Abstract and Keywords
Presentation 2025-02-28 09:00
Dynamic Sensor Selection for Balancing Accuracy and Fairness in Spatio-Temporal Monitoring Systems
Taiyo Nakamura, Koya Sato (UEC) SeMI2024-91
Abstract (in Japanese) (See Japanese page) 
(in English) With the advancement of the Internet of Things, the demand for spatio-temporal data analysis has increased. In spatio-temporal environmental monitoring (e.g., weather and indoor monitoring) increasing the number of sensors improves accuracy; however, it raises observation and communication costs. To balance sensing costs and accuracy, the number of sensors must be limited, and those that ensure interpolation accuracy should be prioritized. Although there have been several discussions on optimizing sensor placement to reduce error, these works often assume sensors remain fixed over time domain once optimized. This approach neglects the issue of sensor lifetime degradation caused by load concentration on specific sensors. In this study, we propose a dynamic sensor selection method based on Bayesian optimization to balance regression accuracy and resource distribution in spatio-temporal environmental monitoring tasks. By incorporating a fairness metric into the objective function, which considers both the error when using selected sensors and the operating frequency of each sensor, we aim to achieve a trade-off between resource distribution and regression accuracy. We show that the proposed method achieves both accuracy and fairness through characterization using indoor environmental and weather data.
Keyword (in Japanese) (See Japanese page) 
(in English) Gaussian Process / Bayesian Optimization / Sensor Selection / / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 384, SeMI2024-91, pp. 36-41, Feb. 2025.
Paper # SeMI2024-91 
Date of Issue 2025-02-20 (SeMI) 
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)
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Conference Information
Committee SeMI IPSJ-UBI IPSJ-MBL  
Conference Date 2025-02-27 - 2025-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SeMI 
Conference Code 2025-02-SeMI-UBI-MBL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dynamic Sensor Selection for Balancing Accuracy and Fairness in Spatio-Temporal Monitoring Systems 
Sub Title (in English)  
Keyword(1) Gaussian Process  
Keyword(2) Bayesian Optimization  
Keyword(3) Sensor Selection  
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1st Author's Name Taiyo Nakamura  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Koya Sato  
2nd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2025-02-28 09:00:00 
Presentation Time 25 minutes 
Registration for SeMI 
Paper # SeMI2024-91 
Volume (vol) vol.124 
Number (no) no.384 
Page pp.36-41 
#Pages 6 
Date of Issue 2025-02-20 (SeMI) 

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