10:45 AM - 12:15 PM
[HDS07-P03] Proposal of Web Application for Developing Predisposed Risks in Our Society based on Crowd-Sourcing Framework
Keywords:Social Predisposition, Urban Planning, Crowd-sourcing
The chain structure of disaster occurrence is defined as natural triggers acting on natural predispositions, which in turn act on social predispositions to cause damage. However, in light of recent disasters, there have been cases in which social assets, which should be treated as social factors, have been triggered to cause damage. Although hazard maps have been developed to recognize the risk of disasters in normal times, social assets that trigger damage, such as those in the previous case, have not been visualized or shared. This is due to the fact that even if risk types could be identified, these assets are numerous and change significantly over time. In other words, greater efficiency is required for investigation and updating. Therefore, in this study, social factors that may trigger damage such as human suffering and blocked evacuation routes due to collapsed utility poles are positioned as "socially predisposed risks". In ordinary time, those objects are essential for our satisfied lives, however at disaster occurrence, those could be risks suffering us. Thus, we aim to establish an efficient method for creating socially predisposed risk maps that visualize these factors. Social predisposition risks are assumed to be of various types and, moreover, to be enormous in number. Therefore, human resources are indispensable. Therefore, we will promote the establishment of a method utilizing crowdsourcing, in which participants are recruited via the Internet and issues are solved by the power of the crowd. In addition, a web application will be developed to provide an environment in which various participants can participate at any time and from anywhere. By integrating the above, we will propose a cost-effective method for creating and updating social risk maps. The web application to be developed in this study is designed and developed with a function for posting photos of socially predisposed risks, a function for registering judgments of socially predisposed risks that can be ascertained from the posted photos, and a function for mapping the judgment results. In particular, since a wide variety of socially-predisposed risks are assumed, the experiment was limited to the four categories of "utility poles," "signboards," "road signs," and "roadside trees" in this study. However, by including an open-ended "other" field, the author hopes to uncover socially predisposed risks that are not assumed by the author. The type of risk can be easily changed on the system. This application was implemented provisionally on the campus server and tested in the "Higashi Chaya-gai" area of Kanazawa City. After that, with the help of five collaborators, we conducted a demonstration experiment in Toyama City. A total of 564 minutes were spent taking pictures of socially predisposed risks, and a total of 165 minutes were spent judging socially predisposed risks. As a result, a socially predisposed risk map for the target area was created at a low cost. On the other hand, these five collaborators were collaborators who understood and agreed with the objectives. Looking at society as a whole, it is not always possible to recruit many collaborators. Therefore, we examined the possibility of making effective use of photographs related to the city that were taken for a different purpose than this objective. As a result, it became clear that these photos also contain socially predisposed risks and can be utilized, although the occupancy rate is low. In the future, we expect to collect more photos containing socially predisposed risks by utilizing various photos published on SNS and the Internet. In addition, we believe that socially predisposed risk maps can be created and updated at a lower cost through the use of AI and other means to identify rough locations and identify risk types.