AI Based Novel Approach for Early Flood Warning Using Android and Iot

Resumen

India has a sub-tropical monsoonal climate characterized by heavy rainfall which in turn causes massive flooding. To avert such situations, it is very important to monitor and receive timely emergency alerts about the flow of water and water level situation based of the riverbed. The main objective of this concept is to design an efficient flood pre-alerting system. This project predicts Floods in advance with the help of emerging technologies, such as MATLAN, Embedded and Internet of Things (IoT) this work develops an IoT-based prototype to collect hydrological data and meteorological data of river water. Hydrological data like water flow, water level, and water discharge along with meteorological data like temperature, humidity, wind speed, and wind direction are used to classify the flood type. In matlab software long short-term memory (LSTM) model is introduced based on calibrated data to yield alerts. Classifications like “no alert,” “yellow alert,” “orange alert,” or “red alert.”