Effective measures against global warming must integrate both mitigating and adaptive strategies. Accordingly, this study aims to develop information systems adapted to flooddamage, such as electricity infrastructures, by using green energy in urban areas. Rapid urbanization has caused significant increases in heavy rain; therefore, people in flood-risk areas need risk information, such as precipitation data and river levels, to help prevent flood damage. However, such people generally cannot recognize the risks of flood damage because existing information only provides observation data or alerts. To reduce flood damage, information must be provided on the risk of massive floods and inundation. Therefore, we propose risk indicators for flood situations. Urbanization exposes people to a variety of infrastructural and individual vulnerabilities. The existing hazard map based on observation data shows the same level of risk for all people in flood-risk areas, leading people to over-or underestimate their risk. In contrast, flood risk indicators can be customizedaccording to individual vulnerabilities. Therefore, we proposea common interface for a communication system to calculate risk indicators based on observation data. This risk indicators show common risk for people at risk situations. Our system collects common risk indicators and customizes them according to three vulnerability factors: environmental, social, or human. Such risk indicators can reflect situationally relative risk levels using real-time data. Disaster prevention agencies can in turn use our risk indicators to assess people'sflood risks. Additionally, social factors such as power failurecan impede the distribution of risk indicators. As immediate estimation requires rapid distribution to vulnerable people, we propose a common communication system interface for the immediate distribution of risk indicators to vulnerable people.