Ryo Ueda, Senior Research Associate
In Japan, frequently affected by natural disasters, fast and effective disaster response is a major challenge. To realize a highly efficient and optimized society utilizing all kinds of social data, the use of real-time data is key to obtaining information and making decisions in the event of a disaster, but progress is slow.
Evacuation delays were pointed out as a contributing factor to the massive human casualties caused by the heavy rainfall disaster in western Japan in 2018. This writer posits that evacuation measures could have been more effective if real-time data were used, and analyzed the evacuation situation at the time of the disaster, based on population data for the Mabicho district. The results showed that real-time data could be used to clearly assess dangerous situations such as people remaining in highly hazardous areas. In addition to currently utilized general evacuation advisories, as part of disaster protection measures and regional policies, it is important to implement more effective disaster prevention when time is limited, such as focusing on evacuation guidance in specific areas based on data.
In addition, the Akemi district in Toyohashi City, one of the major industrial areas in the Chukyo region, was chosen as a research field in order to identify further effective measures. Practical research was conducted to formulate measures that not only use data analysis but also integrate prediction and decision making. In discussions with stakeholders in the area, such as local companies, it was found that road congestion immediately following a disaster is an important issue in the region. Therefore, real time data was used to simulate road traffic congestion forecasting by time of disaster. A model was built representing a more realistic situation, including the consideration of people’s home bound direction, as well as the actual population distribution during day and night, based on resident information and other points from the data. This simulation demonstrated that it is possible to create rules for traffic to assembly points and emergency traffic, considering priority by time or route, instead of general road closures in all areas, by predicting and visualizing road congestion by time. The results were effective in appealing to stakeholders as important suggestions and evidence for regional collaboration.
With the above example model as a starting point, this research paper points out that similar data utilization and efforts are necessary for regional disaster response. It emphasizes that for this purpose a social platform is necessary, and that data management and ICT companies as well as local stakeholders should work together on both systems and their implementation.
The full version of this report is available in PDF format below. This report is only available in Japanese.
Advancement of Disaster Response by Utilizing Real-Time Data ―Towards the Realization of an Autonomous Resilient Society―