Method to measure the effectiveness of new technologies that contribute to reducing damage from natural disasters

Natural disasters pose various challenges to the national land. While various technological innovations have contributed to overcoming these difficulties, there are still many problems that need to be solved to play a preventive role. A framework is needed to examine social design proposals that promote the production of technology. However, in order to implement such an idea in society, a new business model based on non-monetary value and reputation must be developed to address various social issues, including not only disaster prevention but also maintenance and management of social infrastructure and green infrastructure, including agriculture. This research is therefore focused on the concept of adaptive finance, which is a practical approach to finance for adaptation. Therefore, the purpose of this study was to organize basic data and visualize the characteristics of new technologies in order to put the concept of adaptive finance into practice. We examined ways to visualize the effects of new technologies based on a database of new technologies (domestic open data) that have been developed for the maintenance and management of social infrastructure and for disaster prevention and mitigation. In addition, we developed an index to quantitatively evaluate the degree of damage reduction. By doing so, we aimed to clarify how the introduction of new technologies contributes to disaster prevention and mitigation, and to promote their application to actual disaster prevention policies. For this visualization, we used generative AI to create an index based on various technological data. The results of this research will support policy makers, local governments, and private companies in their decisions to introduce disaster prevention technologies and contribute to minimizing disaster damage in the future.