Artificial Intelligence based Subway Rainwater Status Notifier and Disposal System

In this paper, developed a system to detect the level of water in a subway system and predict the hazardous zone and also inform the people to go to another safer zone. Submerge is one of the most destructive natural events that severely damage the ground and inundate underground infrastructure. Underground subway systems inmetropolitan areas are susceptible to flooding, which may be exacerbated when land subsidence occurs. However, previous studies have focused on flood risk evaluation on regional/watershed-scales and land subsidence monitoring in plains, instead of on subway flood risk evaluation and how land subsidence aggravates the flood risk in subway systems. Using theproposed risk indicators and field survey data, present a method assessing the flood risk of metropolitan subwaysystems under a subsidence condition based on the artificial intelligence combined with arduino nano and GSM. The proposed method was used to evaluate the flood risk of the metropolitan subway systems and apprise the people to go secure zones.