IoT Based Flood Detection and Avoidance System

Abstract

In order to lessen the effects of natural disasters, it is essential to identify flooding. Machine learning has become a viable method for predicting floods thanks to the development of technology. Through the analysis of vast volumes of data, such as satellite images, weather forecasts, and historical flood records, Machine learning algorithms can help in the detection of floods. The use of machine-learning methods like support vector machines, decision trees, and neural networks can aid in locating flood-prone locations and predicting the intensity of the flood. Furthermore, these algorithms can be employed to identify the beginning of a flood and send out early alerts to the impacted areas. Combining these technologies will allow for the establishment of a strong flood detection system, which will considerably lessen flood damage. This abstract emphasizes how Machine learning may enhance flood detection and how important it is for reducing the effects of natural disasters.