Artificial Intelligence (AI) has become a tool that, if used correctly, can be extremely helpful, especially for determining or detecting things that are sometimes difficult for us to do easily. So much so, in fact, that it has been an operational tool in the prevention and management of risks from seismic events and natural disasters.
In this context, the events that occurred in the country on June 24th tested our response capacity, highlighting the urgent need for more precise tools for disaster prevention and response.
How does AI work in Disaster Management?
Modern disaster risk management is structured in three fundamental phases supported by algorithms:
Preliminary Phase (Prevention and Early Warning):
Dynamic patterns are analyzed using probabilistic models that process hydrometeorological and seismic variables to issue alerts before the occurrence of severe events.
Response Phase (Real-Time Evaluation):
During an emergency, unmanned aerial vehicles (drones) capture high-resolution images. Convolutional Neural Networks process these visual layers to automatically classify the degree of collapse of critical infrastructure (bridges, roads, buildings), as was done by the Bolivarian Aerospace Agency (ABAE), the Simón Bolívar Geographic Institute of Venezuela (IGVSB), scientists, and surveyors who are still working on processing photographs collected from satellites to reconstruct, study, and evaluate the data, and thus the damage caused by the double earthquake.
Resilient Recovery Phase:
The data generated allows for the construction of digital twins of the territory, optimizing resource allocation and planning a safer reconstruction in the face of future events, and designing earthquake-resistant cities for greater safety of citizens living in the areas most affected by disasters.
Another of these tools is geospatial predictive modeling, which is the use of neural networks applied to topographic and meteorological data to anticipate landslides and river floods and thus design buildings more accurately suited to the country's soils.
This is what image processing through drones in conjunction with AI is all about: Integrating computer vision algorithms with aerial photogrammetry to assess structural damage after earthquakes in record time.
The experience of Venezuela and China demonstrates that international cooperation in AI is key to risk management. While China provides the technological infrastructure and predictive models, Venezuela offers a real-world testing ground in the face of the growing threat of natural disasters. This alliance can not only save lives but also lay the foundation for a new paradigm in global disaster prevention with a Venezuelan touch.
