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Paper Abstract and Keywords
Presentation 2026-03-17 11:55
Indoor Environment Estimation via Participatory Crowdsensing with Incentive Design Incorporating Estimation Uncertainty
So Imamura, Nattaon Techasarntikul, Yuichi Ohsita, Hideyuki Shimonishi (UOsaka) CQ2025-113
Abstract (in Japanese) (See Japanese page) 
(in English) In the development of smart buildings, the high costs of deploying and maintaining dense stationary sensor networks remain a major challenge. While Mobile Crowdsensing (MCS) is a promising solution, conventional "opportunistic" models are restricted by occupants' routine movement paths, leading to persistent sensing "blind spots" and difficulties in continuous fixed-point monitoring.

This study proposes an "on-demand deployment" sensing model that defines humans as agents responsible for placing and collecting sensors according to system requirements. Our methodology employs Gaussian Process Regression (GPR) to estimate the spatio-temporal distribution of the indoor environment. By incorporating the "estimation uncertainty" directly into the incentive design, the system dynamically sets higher rewards for regions with high uncertainty. This approach adaptively guides autonomous human decision-making toward locations with high informational value.

Simulation results using real-world data confirm that the proposed method more efficiently reduces the overall Root Mean Square Error (RMSE) within a limited budget compared to interpolation methods based on stationary sensor spatial averages.
Keyword (in Japanese) (See Japanese page) 
(in English) Mobile Crowdsensing (MCS) / Gaussian Process Regression (GPR) / Uncertainty-based Incentive Design / Indoor Environment Estimation / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 409, CQ2025-113, pp. 67-72, March 2026.
Paper # CQ2025-113 
Date of Issue 2026-03-09 (CQ) 
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 CQ2025-113

Conference Information
Committee CQ MVE IMQ IE  
Conference Date 2026-03-16 - 2026-03-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa-Sangyoushien-Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2026-03-CQ-MVE-IMQ-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Indoor Environment Estimation via Participatory Crowdsensing with Incentive Design Incorporating Estimation Uncertainty 
Sub Title (in English)  
Keyword(1) Mobile Crowdsensing (MCS)  
Keyword(2) Gaussian Process Regression (GPR)  
Keyword(3) Uncertainty-based Incentive Design  
Keyword(4) Indoor Environment Estimation  
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Keyword(6)  
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1st Author's Name So Imamura  
1st Author's Affiliation The University of Osaka (UOsaka)
2nd Author's Name Nattaon Techasarntikul  
2nd Author's Affiliation The University of Osaka (UOsaka)
3rd Author's Name Yuichi Ohsita  
3rd Author's Affiliation The University of Osaka (UOsaka)
4th Author's Name Hideyuki Shimonishi  
4th Author's Affiliation The University of Osaka (UOsaka)
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Speaker Author-1 
Date Time 2026-03-17 11:55:00 
Presentation Time 20 minutes 
Registration for CQ 
Paper # CQ2025-113 
Volume (vol) vol.125 
Number (no) no.409 
Page pp.67-72 
#Pages 6 
Date of Issue 2026-03-09 (CQ) 

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