Floods are considered to be among the most natural disasters, causing severe socioeconomic impacts including loss of human lives, destruction of properties, and disruption of economic activities. Many scholars had proposed and developed different solutions that can prevent floods from occurring.
A group of researchers almost from SIMAD University developed a robust model, a real-time flood detection system based on Machine-Learning-algorithms; Random-Forest, Naïve-Bayes, and J48 that can detect water levels and measure floods with possible humanitarian consequences before they occur.
This flood-detection system gives an immediate response to the authority and near inhabitants before actual floods happen. It informs people about the state of the current water level by using Aurdino-sensor-network, which then provides SMS notification if there is a dangerous situation through the GSM modem.
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