Automated Pump System in Polders and Early Warning for Flood Anticipation Based on Internet of Things and Machine Learning

Project information

  • Category: Embedded, IoT
  • Completion: June 2021 - October 2021

The project titled "Automated Pump System in Polders and Early Warning for Flood Anticipation Based on Internet of Things and Machine Learning" focuses on developing a tool deployed in water polders capable of predicting potential flood occurrences in a region. This prediction is facilitated by machine learning algorithms using input parameters such as weather forecasts from three surrounding areas provided by the BMKG (Indonesia's Meteorology, Climatology, and Geophysics Agency), along with several supporting sensors. Key tasks include training machine learning models with curated datasets and developing an Android monitoring application for remote IoT system monitoring.