| Presentation | 2018-05-24 [Invited Lecture] Video Streaming Method using Object Recognition for IoT Hajime Kanzaki, Kevin Schubert, Nicholas Bambos, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | Industrial IoT / Video streaming / Edge computing / Object Recognition / Optimization / Dynamic Programming |
| Paper # | SR2018-9 |
| Date of Issue | 2018-05-17 (SR) |
| Conference Information | |
| Committee | SR |
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| Conference Date | 2018/5/24(2days) |
| 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 |
| Chair | Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) |
| Vice Chair | Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) |
| Secretary | Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) |
| Assistant | Mamiko Inamori(Tokai Univ.) / Hiroyuki Shiba(NTT) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(NIT, Akashi College) |
| Paper Information | |
| Registration To | Technical Committee on Smart Radio |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Invited Lecture] 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 |
| 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.) |
| Date | 2018-05-24 |
| Paper # | SR2018-9 |
| Volume (vol) | vol.118 |
| Number (no) | SR-57 |
| Page | pp.pp.51-56(SR), |
| #Pages | 6 |
| Date of Issue | 2018-05-17 (SR) |