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| Presentation | 2021-09-08 13:00 Development and Evaluation of an Abnormal Condition Detection System during Snow Removal Operations based on Behavioral Sensing of Operators Kenya Sugimoto, Hiroshi Yamamoto (Ritsumeikan Univ.), Yoshinori Kitatsuji (KDDI Research, Inc.)  IA2021-19 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Snow removal operations by snowplows in Japan's snowy and cold regions play an important role for securing social activities and transportation of local residents. In order to prevent traffic accidents and to provide safety for local residents, it is necessary to perform the snow removal operation as efficiently as possible at night when there is less traffic. However, in regions such as Hakuba Village in Nagano Prefecture where many tourists visit during the winter for skiing and other activities, there are situations where the operation must be suspended at night due to car and pedestrian traffic. In order to improve the efficiency of snow removal operations, it is necessary to take measures such as temporarily restricting traffic of cars and pedestrians by quantitatively identifying the areas where such situations are likely to occur. In our study, we develop a system to detect occurrence of the abnormal conditions during snow removal operations and identify the locations where such conditions are likely to occur so that the operators can operate more efficiently in snow removal operations. The proposed system uses an infrared camera and a depth camera which can observe the motion to steer the snowplow by the operator at night by taking pictures of the handle and lever operated and by accurately estimating the motion. Next, we propose a method to identify the date, time, and location that the characteristics of the snow removal operations are much different from the usual ones by analyzing the time-series data of the motion to steer. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | snow removal support / maneuverability analysis / image processing / infrared camera / depth camera / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 167, IA2021-19, pp. 29-35, Sept. 2021. | |
| Paper # | IA2021-19 | |
| Date of Issue | 2021-09-01 (IA) | |
| 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 | IA2021-19 |
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| Conference Information | |
| Committee | IA |
| Conference Date | 2021-09-08 - 2021-09-08 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Internet Operation and Management, etc. |
| Paper Information | |
| Registration To | IA |
| Conference Code | 2021-09-IA |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Development and Evaluation of an Abnormal Condition Detection System during Snow Removal Operations based on Behavioral Sensing of Operators |
| Sub Title (in English) | |
| Keyword(1) | snow removal support |
| Keyword(2) | maneuverability analysis |
| Keyword(3) | image processing |
| Keyword(4) | infrared camera |
| Keyword(5) | depth camera |
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| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kenya Sugimoto |
| 1st Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 2nd Author's Name | Hiroshi Yamamoto |
| 2nd Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 3rd Author's Name | Yoshinori Kitatsuji |
| 3rd Author's Affiliation | KDDI Research, Inc. (KDDI Research, Inc.) |
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| Speaker | Author-1 |
| Date Time | 2021-09-08 13:00:00 |
| Presentation Time | 25 minutes |
| Registration for | IA |
| Paper # | IA2021-19 |
| Volume (vol) | vol.121 |
| Number (no) | no.167 |
| Page | pp.29-35 |
| #Pages | 7 |
| Date of Issue | 2021-09-01 (IA) |
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