Data-Driven AI Systems Can Defeat Natural Disasters

Annual wildfires are no longer coincidental natural disasters. While ignition factors such as carelessness by hikers remain problematic, the fundamental causes of large-scale wildfire spread lie in structural conditions including dry climate, strong winds, inadequate forest management, and urban expansion. Disasters have now evolved into complex crises combining social and climatic factors beyond single phenomena.

As disaster frequency and intensity accelerate, the greatest obstacle is the fixed notion that "disasters cannot be predicted." If we remain in a post-incident response system focused only on aftermath management, we cannot escape the cycle of wildfire damage. The perspective on disaster management must fundamentally change. Now is the time to shift the paradigm from post-recovery focus to predictive and preemptive response using digital technologies such as artificial intelligence and data.

The key is data-based scientific prediction. Comprehensive analysis of satellite imagery, meteorological data, forest humidity, wind direction, and topographical information enables precise prediction of wildfire probability and spread paths. Current prediction accuracy stands at approximately 76%, but gradual advancement must continue to reflect exceptional sudden situations. Identifying high-risk areas in advance and securing response golden time through scientific prediction is no longer a distant future story.

Recently, models incorporate not only environmental variables but also human activity. Social factors such as hiker movement routes and usage patterns in urban-adjacent areas are included in risk calculations, further enhancing prediction precision.

Digital twin-based simulation is also evaluated as innovative progress. Spread scenarios are derived in virtual spaces identical to actual terrain, reflecting wind direction and forest fuel characteristics.

The government plans to advance these technologies, raising wildfire prediction accuracy from the current 76% to 88% by 2027 and completing an AI-based "intelligent wildfire suppression decision-making system" by 2030. This system will propose optimal suppression and evacuation strategies within 60 seconds of wildfire occurrence. Once established, vulnerable groups including the elderly can be evacuated up to 8 hours before fire line arrival, with stable evacuation of all local residents possible 5 hours in advance. Citizens will also be able to check real-time risk information from their locations.

Wildfires are not simply a matter of burning trees. If communication base stations or transmission lines are destroyed, the disaster can expand into a digital catastrophe paralyzing information and communication services across entire regions. Therefore, an integrated management system that rapidly deploys mobile base stations during large-scale disasters and analyzes infrastructure failure possibilities in advance is essential. Defending against both physical and digital damage simultaneously is the core challenge of modern disaster response.

In the AI era, wildfires are no longer force majeure disasters. We have sufficient meteorological data and world-class technological capabilities. The remaining task is institutional mechanisms and implementation will to connect these with safety systems. To build a system that operates preemptively 365 days a year, I am promoting the enactment of a "Digital Disaster Safety Management Act." The purpose is to enhance national digital resilience through integrated management of prevention, preparation, response, and recovery, while institutionalizing AI-based analysis.

A predictable and resilient society enhances industrial stability and protects citizens' daily lives. A digital-based disaster response system will become core infrastructure supporting Korea's sustainability, beyond mere safety measures.