Proceedings of the International Joint Conference on Science and Engineering (IJCSE 2020)

Early Warning System for Flood Disasters Using the Internet of Things

Authors
Yuyun, Hamka Zulfaesa, Latief Arda Abdul
Corresponding Author
Yuyun
Available Online 24 November 2020.
DOI
https://doi.org/10.2991/aer.k.201124.002How to use a DOI?
Keywords
Flood, Early Warning System, MCU8266, Fuzzy Inference System, HC-SR04
Abstract
Floods are one of the most frequently occurring natural disasters in Indonesia. It is therefore of special concern to reduce the risk of flood fatalities and other damage. The purpose of this study is to design a flood early warning system based on the Internet of Things (IoT). In this work, we use an ultrasonic HC-SR04 sensor to collect information about water levels. Further, we use an MCU8266 node as a microcontroller to analyze the sensor data and test it using a fuzzy inference system (FIS). To monitor the server activities, a Blink application is used as an iCloud IoT to hook up to smartphone devices. The test results show that all the devices function properly and that the system can classify water levels into normal, standby, alert, and danger categories in real time. Thus, the server can send information to the output device before a flood disaster occurs.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the International Joint Conference on Science and Engineering (IJCSE 2020)
Series
Advances in Engineering Research
Publication Date
24 November 2020
ISBN
978-94-6239-276-2
ISSN
2352-5401
DOI
https://doi.org/10.2991/aer.k.201124.002How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yuyun
AU  - Hamka Zulfaesa
AU  - Latief Arda Abdul
PY  - 2020
DA  - 2020/11/24
TI  - Early Warning System for Flood Disasters Using the Internet of Things
BT  - Proceedings of the International Joint Conference on Science and Engineering (IJCSE 2020)
PB  - Atlantis Press
SP  - 8
EP  - 12
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201124.002
DO  - https://doi.org/10.2991/aer.k.201124.002
ID  - Yuyun2020
ER  -