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DESIGNING A LEARNING ASSISTANCE ENVIRONMENT FOR PROLONGED EVACUATION LIFE WITH EDGE DEVICES IN THE ERA OF MASSIVE NATURAL DISASTERS
1 Shikoku University (JAPAN)
2 Tokushima University (JAPAN)
About this paper:
Appears in: EDULEARN21 Proceedings
Publication year: 2021
Pages: 9829-9833
ISBN: 978-84-09-31267-2
ISSN: 2340-1117
doi: 10.21125/edulearn.2021.1992
Conference name: 13th International Conference on Education and New Learning Technologies
Dates: 5-6 July, 2021
Location: Online Conference
Abstract:
The threat of natural disasters such as torrential rain and massive flood is increasing year by year. Typhoon Faxai which occurred in September 2019, landed in the Kanto region in Japan with the strongest force ever observed. Faxai caused torrential rains and massive floods in a short period of time, which disrupted the road network in the area. This effect caused a large-scale blackout in Chiba Prefecture in Kanto region for about 3 weeks. The disconnection of the mobile phone network and other communication networks continued longer than large-scale power outages. Typhoon Hagibis which landed in Japan in October, caused record heavy rain in the Kanto Koshin and Tohoku regions. Climate change makes tropical cyclones more and more violent, and the damage is clearly getting bigger. The report of World Meteorological Organization describes, 2019 was the second warmest year on record so far. The global average temperature in 2020 is also certain to exceed the previous record.

About a month and a half after the massive flooding caused by Typhoon Hagibis, about 600 people from 245 households were staying at the evacuation centers in the affected area of Nagano City. In addition, Nagano City Hall continued to operate the shelter until the end of 2019. Fukushima and Miyagi prefectures continued to operate shelters, as did Nagano City. In the Great East Japan Earthquake that occurred in 2011, more than 20,000 victims continued to live in evacuation centers at 73 evacuation centers even seven months after the disaster. In natural disasters caused by climate change and disasters caused by huge earthquakes and tsunamis, it is inevitable that the evacuation period will be prolonged.

Due to changes in the phase of evacuation life, the proportion of daily life such as resuming studying in the evacuation life gradually increases. This "daily life under the non-daily life" will continue until they leave the evacuation center. Generally, shared Wi-Fi service is installed at evacuation center. However, these communication environments have high latency and the communication is interrupted due to normal evacuees collect disaster information. The current e-learning environments can always communicate, and it is built on the premise of a high-speed and low-latency communication environment and is not suitable for use in these low-quality communication environments. We must construct an e-learning environment that assumes a low-latency communication environment with unstable connection conditions under the disaster situation.

In this study, we design an asynchronous learning assistance framework for disaster situations. We implement a feature-limited LMS service using a power-saving IoT device. This IoT device is equipped with Wi-Fi capabilities and behaves as an access point for a limited number of users. The IoT device will function as an edge device that integrates a limited function version of the LMS and a communication status monitor. This learning assistance framework based on custom edge device behaves as if a stable internet connection is maintained even if the internet connection is lost. We aim to support the continuous use of e-learning in “daily life under the non-daily life” from the middle to the end of evacuation shelter life. Additionally, we explain the design of learning assistance framework for disaster situation, and it is explained the experimental results of the execution environment implemented as a prototype, and effectiveness.
Keywords:
e-learning, disaster reduction, edge computing, unstable communication conditions.