Challenges in Evacuation Behavior During Disasters and Support for the Elderly Revealed by Data Analysis
Enhancing evacuation support for the elderly by analyzing crowd movement data to understand behavior patterns during disasters.
A construction consultant analyzed human flow data to evacuation sites during flooding using "Hourly Visits" and identified evacuation behavior patterns during disasters. It was confirmed that after an increase in checking evacuation sites in the evening, there was a tendency for revisits to increase due to the intensity of the rain. Additionally, analysis using "demographic ratios" revealed that the evacuation rate among the elderly is low, suggesting that evacuation support measures for the elderly are necessary for future disaster response. ■ Visualization of evacuation behavior patterns during disasters using data ■ Analysis of the evacuation rate of the elderly to identify issues ■ Utilization of human flow data to evacuation sites to gain insights for future disaster measures ■ Clarification of the need for evacuation support measures for the elderly ■ Possibility of planning effective evacuation guidance and support measures based on data
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Our mission is to utilize AI to analyze location-based big data, combining and visualizing a wide variety of location and spatial information so that anyone can make use of it. By visualizing the "flow of people in the real world," we aim to contribute to solving issues such as resource waste, inefficiency, and environmental destruction in society, industry, and daily life. Please feel free to contact us if you have any requests.
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