A NOVEL APPROACH FOR EARLY FLOOD WARNING USING ANDROID AND IOT
Keywords:
Internet of Things, meteorological data, Temperature, humidity, wind speed, orange alert,”, “red alert, long short-term memory.Abstract
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.”
