Flood Identification with Fuzzy Logic Based on Rainfall and Weather for Smart City Implementation

Abstract

Flood is one of the problems that often occur in big cities, one of which is Surabaya. This arises due to various factors, including changes in land use, relatively high rainfall, and an inadequate drainage system. Floods in several places in Surabaya are basically caused by the unavailability of ditches and places to drain rainwater. This causes rainwater to fall directly onto the road and cause air impacts. One way to anticipate flooding is to know the conditions that trigger flooding, namely rainfall and air temperature. In this study, a classification system for the level of rainfall and air temperature is proposed which affects flooding. The method we propose is fuzzy logic with the Mamdani approach. Our data set is real temperature and rainfall data in the city of Surabaya from 2017 to 2020. The test results from our proposed method, it can be analyzed that fuzzy logic can also study the relationship and degree between temperature and rainfall so as to result in the condition of the city in that month to predict there will be flooding or not.