AI in Emergency Response: Turning Data into Action

Most cities plan disaster recovery after the damage is done. This one plans it first 🌊 Resilio City is an AI application built with NitroStack that simulates disasters like floods and earthquakes on a city's road network, then generates a prioritized, budgeted recovery plan before disaster ever strikes. Watch the complete video here: https://lnkd.in/dufw7qw7

AI weather-prediction expert Amy McGovern was in the The New York Times this week commenting on Google-led AI developments, and how they're advancing hurricane prediction -- it's becoming clear that weather research is a field where AI, of various stripes, is living up to the lofty expectations. The article, with a gift link, is in her post below. Earlier this year, she dove even more deeply into the state of AI weather prediction, in her interview with "Someday, in Science". You can check it out here:  https://lnkd.in/enz4vQDk

Did a blog this afternoon on AI models forecasts for a few systems across the Atlantic and Pacific basins, including #TD5, #Lowell, and #95E. https://lnkd.in/ezvYBJ_T With Daniel Rothenberg and Brightband

Even images of natural disasters are now being faked with AI. The real question is: how quickly can we build a culture of verification strong enough to stop these fakes from becoming the first version of reality millions of people see? Because when the ground is shaking and the waters are rising, misinformation is no longer just an internet nuisance. It can become part of the disaster itself. https://lnkd.in/gQ8hv_7V #Nepalfloods #AIForReal

New AI models blog focused on the potential area of interest over the Central Atlantic. Google DeepMind has been pretty aggressive on development while most other models are not showing anything. Will the model score a coup in early detection, or will this be a false alarm? https://lnkd.in/eGgZ3m3U With Daniel Rothenberg and Brightband

The most important outcome of Europe's new AI pilots may not be the AI itself. What caught my attention in the EU's new public-sector GenAI initiatives is not the technology, it is the emphasis on 🔄 reusability. Whether it's EUNOMIA.AI, EuropAI or FLOODS & DROUGHTS, the objective goes beyond individual pilots. The projects are building shared frameworks, implementation blueprints, governance models and reusable components that can be adopted across public administrations. That addresses one of Europe's most persistent digital challenges: how to avoid solving the same problem 27 different times. The initiatives point towards a different model: • Shared procurement • Shared technical components • Shared compliance approaches • Shared implementation knowledge In other words, creating mechanisms that make trustworthy AI easier to adopt across Europe. The real opportunity is not deploying AI in a handful of administrations, it is creating repeatable models that allow hundreds of administrations to adopt AI in a compliant, interoperable and operationally sustainable way. Europe does not need more digital ambition alone. It needs implementation models that can be reused at scale. #DigitalGovernment #PublicSectorAI #Interoperability #DigitalSovereignty https://lnkd.in/dzA3J9gi

Crisis decisions cannot wait for a complete damage assessment. Anila Qehaja of UNDP shows how RAPIDA combines satellite imagery, AI, geospatial analysis and field evidence to support recovery decisions within 72 hours. https://lnkd.in/enZ6N9Aa

September is National Preparedness Month and this year's theme, "Americans Stand Ready," is a reminder that readiness starts before an emergency happens. It means equipping emergency managers with the tools, training, and information they need to respond when it matters most.   That’s why we released the AIDE Report, to provide the emergency management community with research and insights on how AI can support their work.   Explore the AIDE Report: https://lnkd.in/es8pfj2Y

People who provide local disaster response and resilience in their own communities already struggle enough with the lack of support and investment, but now everyone also have to deal with fake images and video reporting created with AI. https://lnkd.in/gi2VcZ7R

🌧️ AI for smarter rainfall forecasting and urban flood management Our latest research highlight explores how Sequential Momentum Gradient Descent (SMGD) can improve Artificial Neural Network training for rainfall prediction. Key results: • 94.7%–95.6% prediction accuracy • More than 50% reduction in training time • Improved learning stability and adaptability to changing weather patterns 🎥 Watch the research summary: https://lnkd.in/dVZrh46w Researchers are welcome to submit their research to the Journal of Computer Science. #ArtificialIntelligence #MachineLearning #RainfallForecasting #FloodManagement #DeepLearning #AcademicResearch