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Ardi Syawaldipa
Department of Information Technology, Politeknik Negeri Padang, Padang 21562, INDONESIA
Mechanical Engineering

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A Framework of image processing and machine learning utilization for flood disaster management Fazrol Rozi; Indri Rahmayuni; Ardi Syawaldipa; Fitri Nova; Primawati Primawati; Batara Batara
Teknomekanik Vol 5 No 2 (2022): Teknomekanik
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (238.609 KB) | DOI: 10.24036/teknomekanik.v5i2.17372

Abstract

Flood is one of the annual disasters in many places. It has not been well-managed yet both pre-disaster and post-disaster. Image processing and machine learning are commonly utilized for disaster management systems such as forecasting any potential flood by monitoring the water level in rivers and dams. However, it has a limited framework to be implemented as a strategic plan in flood management. Thus, this study aims to develop a framework for image processing and machine learning utilization for flood management. This study involves Padang, West Sumatera, Indonesia as a sample. It was conducted in three stages; 1) categorize the strategic plans and policies; 2) gather relevant literature; 3) analyze data. As findings, this study proposes a framework consisting of enhanced disaster preparedness, improved coping capacity, and completion of post-disaster reconstruction and rehabilitation. Involvement of the government, researchers and industry are mandatory. Government and researchers should collaborate to establish policies and regulations. Researchers should conduct studies with financial support from the industry. Meanwhile, the industry should be a public-private partnership with the government. In addition, the involvement of the private sector and the government are important factors that must exist to support research in this field.
Co-Authors - Primawati Batara Batara Fazrol Rozi Fitri Nova Indri Rahmayuni