Artificial intelligence can help early warning systems

It is an opportunity, they said, for collaborative efforts, from the global to the local level, to improve predictions of natural phenomena on a global scale by not requiring a huge supercomputer.

They added that machine learning is vital for improving current and near-term forecasts, as it enables automatic detection and offers various applications, such as air quality assessment.

In this context, the experts stressed that the private sector, specifically technology companies, can play a leading role in achieving early warnings for all.

An example of what can be achieved with artificial intelligence and high-resolution satellites is mapping populations at risk and assessing damages after a disaster, as happened in the case of the earthquake that struck Turkey this year.

According to the Vice-Chair of the Thematic Group on Artificial Intelligence and Natural Disaster Management, Elena Exoblaki, made up of the World Meteorological Organization, the International Telecommunication Union and the United Nations Environment Programme, it is necessary to adapt to evolving technologies and, at the same time, address the changing needs and priorities in this field. .

He explained that the aim is to support the early warnings initiative for all, especially in vulnerable areas and hotspots of climate change, which requires scientific efforts with specific research on regions and risks.

Xoplaki said that a new project will provide new solutions to ensure timely, accurate and accurate financial forecasting and impact of extreme weather events and natural hazards.

RO/CRC