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Design and Development of Real-Time Video Transmission System Using Visual IoT Device

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Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2018)

Abstract

Visual Internet of Things (IoT) is a class of IoT that collects rich visual data over the Internet. In general, the visual IoT device is equipped with video transmission equipment such as a mobile camera. Both advanced video transmission techniques and information extraction from images by image recognition techniques are key techniques for the visual IoT. However, since the video data size is larger than the sensor data size in general, one of the issues of visual IoT is high-performance video transmission in networks in which the bandwidths are limited. In this paper, we design a real-time video transmission system using visual IoT device. Our system is based on a novel protocol, named high-performance video transmission (HpVT), for field monitoring via 4G LTE mobile networks. Our implementation of the system is based on Raspberry Pi boards, which are single-board computers with ARM processor. We evaluate the performance of our system in real fields to conclude that we can achieve full high-definition (full HD) resolution video transmission with as high frame rate as 30 fps even from a vehicle moving on a highway.

This research and development work was supported by the MIC/SCOPE #165009001 and JSPS KAKENHI Grant Number JP17K00158. We also thank Inoue computer service, Japan to develop the system in this work and thank Economical Co., Ltd., Japan to provide us with a set of SIM modules. The 3D printer cases are designed by HalloweenJack, Co., Ltd., Japan.

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Notes

  1. 1.

    Python is an interpreted high-level programming language for general-purpose programming.

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Correspondence to Ken T. Murata .

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Murata, K.T., Mizuhara, T., Pavarangkoon, P., Yamamoto, K., Muranaga, K., Aoki, T. (2018). Design and Development of Real-Time Video Transmission System Using Visual IoT Device. In: Kaenampornpan, M., Malaka, R., Nguyen, D., Schwind, N. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2018. Lecture Notes in Computer Science(), vol 11248. Springer, Cham. https://doi.org/10.1007/978-3-030-03014-8_25

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  • DOI: https://doi.org/10.1007/978-3-030-03014-8_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03013-1

  • Online ISBN: 978-3-030-03014-8

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