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Flood disaster warning system on the go

Abdullahi, Salami Ifedabo and Habaebi, Mohamed Hadi and Abdul Malik, Noreha (2018) Flood disaster warning system on the go. In: 2018 7th International Conference on Computer Communication Engineering (ICCCE2018), 19th-20th September 2018, Kuala Lumpur.

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Floods are one of the top natural disaster that affects many regions around the world, harming human lives and lessening economy growth. Therefore, it is crucial to build an early warning system that forecast flow rate and water level to reduce the casualties of flood disaster. The objective of this paper is to design a flood monitoring system which integrates both flow and water level sensor and use two class neural network to predict the flood status from stored data in the database. A laboratory experiment was carried out to simulate the system and a pressure gauge was utilized to measure the pressure of inflowing water. A NodeMCU ESP8266 enables transmission of sensor data to Thingspeak channel for real-time visualization and storing the data in database. Furthermore, two class neural network module built in Microsoft’s Azure Machine Learning (AzureML) was used to predict flood status according to a pre-define rule. The result of the 2-class neural network showed that using 3 hidden layers has the highest accuracy of 98.9% and precision of 100%.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 6727/67951
Uncontrolled Keywords: Azure Machine Learning; 2-class Neural Network; Artificial Neural Network; Azure Web Service; Internet of Things (IoT); NodeMCU (ESP8266); Thingspeak; Flood Forecasting; Flood Monitoring System, Energy Security
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr. Mohamed Hadi Habaebi
Date Deposited: 05 Dec 2018 09:29
Last Modified: 17 Aug 2019 12:33
URI: http://irep.iium.edu.my/id/eprint/67951

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