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| Presentation | 2018-05-24 16:05 [Invited Lecture] Video Streaming Method using Object Recognition for IoT Hajime Kanzaki (Hitachi), Kevin Schubert, Nicholas Bambos (Stanford Univ.)  SR2018-9 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Wireless video applications for Industrial Internet Of Things (IoT) are expanding into a multitude of new services. In the example of cloud processing for visual object detection, a camera is connected to the cloud via a local server and a data network, allowing the processing load to be handled in a distributed manner. This service model heavy taxes the data network with potentially unneeded traffic, thus degrading the overall quality of service for all users on the network. Edge computing techniques mitigate the degradation of service quality by partially processing the sensor data at the local server before the data is transmitted to the cloud. This is done according to the level of interest of the captured data which is categorized by machine learning algorithms. However, conventional edge computing is not optimally efficient as further recognition attributes of the captured object data are not considered. This paper presents a model that adds control of the camera video rate by considering the attributes of captured object. We then investigate cost tradeoffs using dynamic programming, and evaluates the behavior of proposed method under wireless channel condition using NS-3 simulations. Our results show that by adding intelligent adaptive video rate control to the cloud processing of video data capture can reduce overall system power use while improving system efficiency and subsequently network throughput. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Industrial IoT / Video streaming / Edge computing / Object Recognition / Optimization / Dynamic Programming / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 57, SR2018-9, pp. 51-56, May 2018. | |
| Paper # | SR2018-9 | |
| Date of Issue | 2018-05-17 (SR) | |
| 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 | SR2018-9 |
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| Conference Information | |
| Committee | SR |
| Conference Date | 2018-05-24 - 2018-05-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo big sight |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Technical Exhibition, Machine Learning, AI |
| Paper Information | |
| Registration To | SR |
| Conference Code | 2018-05-SR |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Video Streaming Method using Object Recognition for IoT |
| Sub Title (in English) | |
| Keyword(1) | Industrial IoT |
| Keyword(2) | Video streaming |
| Keyword(3) | Edge computing |
| Keyword(4) | Object Recognition |
| Keyword(5) | Optimization |
| Keyword(6) | Dynamic Programming |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Hajime Kanzaki |
| 1st Author's Affiliation | Hitachi (Hitachi) |
| 2nd Author's Name | Kevin Schubert |
| 2nd Author's Affiliation | Stanford University (Stanford Univ.) |
| 3rd Author's Name | Nicholas Bambos |
| 3rd Author's Affiliation | Stanford University (Stanford Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-05-24 16:05:00 |
| Presentation Time | 25 minutes |
| Registration for | SR |
| Paper # | SR2018-9 |
| Volume (vol) | vol.118 |
| Number (no) | no.57 |
| Page | pp.51-56 |
| #Pages | 6 |
| Date of Issue | 2018-05-17 (SR) |
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