Advancing Flood Disaster Mitigation in Indonesia Using Machine Learning Methods
Hammam Riza, Eko Widi Santoso, Iwan Gunawan Tejakusuma, Firman Prawiradisastra
Abstract
The fourth industrial revolution essential components which include cloud computing technology, artificial intelligence, big data, and the internet of things has also been affecting the flood disaster mitigation strategy worldwide. This is also true for Indonesia where the flood disaster event has increased almost three times during the past fifteen years. In this literature review, the advancement of the application of artificial intelligence, in particular, machine learning in flood mitigation in Indonesia is studied. Based on this study, the future possible improvement of flood mitigation has also been given. The study revealed that machine learning has not yet been applied extensively in flood disaster mitigation in Indonesia. Some applications are for rainfall, river water level, and discharge level predictions, and to a lesser degree for flood forecasting and early warning. The future prospective advancement of flood disaster mitigation is the application of machine learning methods in an integrated flood prediction and early warning that covers rainfall, river water level, river discharge, and flood predictions as well as estimated spatial flooding area, and early warning dissemination using the internet of things.