Web-based Riverbank Overflow Forecasting and Monitoring System

Abstract

River overflowing is a common problem in the Philippines. And knowing the fact that we lack proper devices and systems to monitor the water flow makes it even more disturbing. Therefore, this project is to develop a prototype that will measure, monitor, and forecast the water level and the volume of water flowing through the riverbanks. The proponents used Agile development method includes systematic process of designing, developing the prototype, evaluating instructional programs, and system that must meet the criteria of the effectiveness of the project. The prototype consists of algorithms that is performed to have a reliable data. In measuring the river parameters, Wireless Sensor Network (WSN) Algorithm is used to interconnect the sensor nodes in different area of the riverbank. In forecasting, the device performed a machine learning by gathering raw data to run in Voting Algorithm. In monitoring, the prototype provides Cabuyao River Monitoring System (CRMS) a web-based application that uses a Decision Tree Algorithm that will give information and warning to the community. This device and system aim to give early warnings to the communities being both in a timely and systematic way, providing advanced information on its behavior to better prepare the disaster team and government.