HORIZON-CL5-2026-10-D6-09 Road Safety and resilience of rural areas - Collaboration Offer

Dogus Teknoloji proposes to develop AI-based disaster spread models, aimed to satisfy the following call outcome:

- GIS-based application to assist local and regional authorities in identifying and mapping the impact of extreme weather phenomena and other natural disasters (such as floods, fires, storms, heavy snowfall etc.) on the safety and resilience of the road network in their jurisdiction.

By enhancing the GIS-based applications via integrating predictive analytics for wildfire and flood spread, we aim to offer local and regional authorities actionable insights on the potential impact of extreme weather and natural disasters on road networks.

These AI-based models will:

• Utilize remote sensing datasets to study past wildfire or flood events.

• Identify spread patterns, intensity, and affected zones.

• Develop models to simulate how similar events could propagate in areas near critical road infrastructure and rural zones.

• Estimate potential damage extent and identify high-risk segments.

• Overlay predictive insights on the GIS platform to visualize risk zones.

• Enable scenario-based planning for emergency response and infrastructure reinforcement.

These models will lead to improved situational awareness for authorities, data-driven decision-making for road safety and resilience and enhanced preparedness for future extreme weather events.