Adaptive IoT Enabled Flood Management System: An Artificial Intelligence Approach
Himanshu Rai Goyal, Kamal Kumar Ghanshala, Sachin Sharma
Abstract
Flood control is one of the most important areas where practical measures have been implemented to minimise damage. We are developing an IoT-enabled adaptive AI technique for efficient fluid management in this research project. In recent years, floods in Kerala, India, have caused significant damage to people, infrastructure, and the environment. Precipitation rates, temperature, and other data were collected by various IoT devices. Data on floods in Kerala is collected and sorted into two categories: 80% for training and 20% for testing. Six different machine learning models are trained, and the proposed hybrid model achieves a maximum accuracy of 99.64%. We were able to avoid losses as a result of integration.