Japan Geoscience Union Meeting 2021

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[J] Oral

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI34] Earth and planetary informatics with huge data management

Thu. Jun 3, 2021 9:00 AM - 10:30 AM Ch.03 (Zoom Room 03)

convener:Ken T. Murata(National Institute of Information and Communications Technology), Susumu Nonogaki(Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology), Rie Honda(Department of Science and Technology, System of Natual Science, Kochi University), Keiichiro Fukazawa(Academic Center for Computing and Media Studies, Kyoto University), Chairperson:Keiichiro Fukazawa(Academic Center for Computing and Media Studies, Kyoto University), Ken T. Murata(National Institute of Information and Communications Technology)

9:00 AM - 9:15 AM

[MGI34-01] Development of snow detection techniques by using visual IoT

*Yuki MURAKAMI1, Ken T. Murata1, Shigeto Watanabe2 (1.National Institute of Information and Communications Technology, 2.Hokkaido Information University)

Keywords:Visual IoT

There is low-cost single board computer such as Raspberry Pi, Arduino, etc., and it can connect the cloud service through the Internet. The single board computer is expected as architecture for Internet of Things (IoT), and many users connect sensors and actuators to the computer. Visual IoT is a kind of IoT, and it is remote sensing method to extract information from image and/or video data in real time. Video transmission is not easy in low-band network like mobile environment, it is practical method to transmit extracted information in real time to cloud server through mobile network. In other words, remote camera is used as remote visual sensor instead of video transmitter. We selected snow detection as one of visual IoT applications. We developed and tested basis algorithm for snow detection. In test, we used field camera set up in Ebetsu city (Hokkaido prefecture) and Chikuma city (Nagano prefecture), and we focused on detection of trigger when snow fall begin or end. Now, we report abstract of the algorithm and test results.