A Fuzzy Expert System for Identifying and Preventing Flood Damage using the Internet of Things

Abstract

When it comes to managing floods, flood control has proven to be crucial. Installation of rock berms, sandbags, preserving normal slopes with vegetation, and building or enlargement of drainage channels are all methods used for this. Research in this field has begun to concentrate intently on drainage systems following Katrina (2005). Though several researchers have created and erected drainage systems of varying designs, the issue remains unresolved. Therefore, two cellular automata (CA)-based grid structures—a hexagonal one and an octagonal one—are presented in this study. Another solution to the problem of flooding and waterlogging is a method presented for determining the optimal grid design for a drainage system. This study examines and contrasts three distinct grid patterns: a square grid, a hexagon grid, and an octagon grid. The flood plain's linear and bilinear heights have been compared. This analysis led to the recommendation of a grid layout with the tanks located at the four corners of the drainage system. The suggested approach for creating the drainage system has been tested, and shown to be valid, with the use of the Paired T-Test. The researcher has responded to this need by proposing Internet of Things (IoT) and AI-based flood detection methods. Most often, the Internet of Things, wireless sensor networks, and metropolitan area networks are utilised to spot floods. Out of these three, IoT is the most effective technology for communicating and analysing the issue at hand.