Review Paper on IoT Based Flood Prediction Model

The importance of environmental monitoring is undoubted in this age. Knowledge of environmental monitoring is important to determine the quality of our environment. Information gathered through environmental monitoring is important to many different decision makers. So it is necessary to develop a system that monitors the environment conditions or the ambient conditions in real-time. The Internet of Things (IoT) is a field of embedded systems and computing where number of devices collectively gathers data in real time and transfers it through a Wireless Sensor Network (WSN) to the computational devices for processing and analysis. IoT generally combines embedded system with cloud computing and analyzing platforms. Of all the natural disasters, floods are the most common of them, and cause significant damage to life, infrastructure, and agriculture. Researchers and scientists have moved on from physical parameter based flood prediction to mathematical modeling based flood prediction schemes, and now the methodologies are focused around algorithmic approaches. In this work, an IoT and machine learning based embedded system is proposed to measure different atmospheric conditions to predict the weather information like temperature, pressure, humidity, wind speed and direction, rainfall etc and predict the upcoming natural disasters like floods after analyzing the trend of climate change. The proposed system uses a mesh network connection over ZigBee for the WSN to collect data, and a Wi-Fi module to send the data over the internet and also consumes low power. The data sets from array of sensors are recorded and monitored using cloud database and processed using an artificial neural network model to forecast the different weather events and predict the upcoming disasters.