Low Cost IoT based Flood Monitoring System Using Machine Learning and Neural Networks: Flood Alerting and Rainfall Prediction
Dola Sheeba Rani, G Naragund Jayalakshmi, Vishwanath P. Baligar
Abstract
The term Internet of Things [IoT] refers to the ever expanding complex system of basic things that emphasize communication between computing objects, devices and systems by offering connectivity from anyplace and at any time. It is estimated that by the end of 2020, 50 billion devices are said to be connected. IoT technologies play a crucial role to encompass many smart applications in real life. On the other hand, the crosscutting nature of IoT components and systems, introduce new security challenges. IoT covers advantages for various fields like agriculture, industry, healthcare, automobiles and home automation for improving and automating various day-to-day activities. Flood is usually caused either by change in the state of water body or due to the overflow of rivers, dams, etc. Due to advanced civilization and improved human life, environment problems also tend to increase. This paper includes the effective and flexible method for the detection of flood and alerting system. The most advanced technologies like machine learning (ML) provide significant boon to the field of technology are very powerful in monitoring the normal and abnormal behavioral characters of any machine. The objective of this work is to survey on flood issues. Neural networks are most popular, widely used for rainfall forecasting and perform efficiently.