A flood monitoring and forecasting model supported by cameras and ultrasonic sensors

• Grant number: 24/07514-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2024
• End date: July 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Jó Ueyama
• Grantee: Otávio Ferracioli Coletti
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID

Abstract

Floods affect many cities across the country and cause a great variety of material and human damage. For this reason, researchers have been working on monitoring and forecasting floods in order to reduce this damage. Various approaches to measuring water levels have been used in this context, most of which are techniques applied to known characteristics of the watercourse in order to somehow measure the height of the water in a river or stream. Therefore, this project aims to help with this monitoring by developing and applying solutions to improve flood detection using a set of sensors and machine learning techniques. Considering the task of predicting floods from information such as the height of the watercourse from an ultrasonic sensor and from images from video cameras, the aim is to advance a solution to carry out this prediction using machine learning techniques.