Researchers aim to use AI to guide disaster response through social media scans

By Ademola Adesokan
University of Missouri University of Science and Technology, Conversation

Laura, Missouri – When a disaster occurs – hurricanes, wildfires, earthquakes, etc. – It counts every second. Emergency teams need to find people quickly, send help, and stay organized. In today’s world, one of the fastest ways to get information is to go through Social Media.

In recent years, researchers have explored ways that artificial intelligence can help with social media in emergencies. These programs can be Scan millions of posts Sites such as X, Facebook, Instagram. However, most existing systems are looking for simple patterns such as keywords and damage images.

In my research AI ScientistI have developed a new model that goes further. They can understand The meaning and context of the post – What researchers call Semantics. This helps the system identify people in need and improve the way situational awareness information is categorized in emergencies. The results show these tools You can give a clear view to the rescue team What’s going on on earth and where do you need help?

From posts to lifesaving insights

People share Billion Posts Every day on social media. During disasters, they often share photos, videos, short messages, and even locations. This creates a huge network of real-time information.

But there are so many posts that it’s hard for people to find what’s important right away. That’s where artificial intelligence comes in handy. These systems to use Machine Learningyou can scan thousands of posts every second, find urgent messages, find spot damage shown in photos, and convey actual information from rumors.

People during Hurricane Sandy in 2012 Over 20 million tweets have been sent Over 6 days. If AI tools were used, they might have helped them find people at risk faster.

Training AIS

Researchers start Teach AI programs to understand emergencies. In one study I conducted, I saw thousands of social media posts from disasters. I categorized them into groups like people seeking help, damaged buildings, general comments. Then I trained the program using these examples Sort new posts by themselves.

One major step forward was teaching programs to view photos and words together. For example, photos of flooded streets and messages like “We’re trapped” are stronger signals than either alone. Using both, the system has become much better at showing people where they need help and how serious the damage is.

Finding information is just the first step. The main goal is to help emergency teams act quickly and save lives.

I work with the US emergency response team Add this technology to your system. When a disaster occurs, my program can use social media posts to show where you need help. You can do that too Classify this information as urgentlyhelping rescue teams use their resources where they need it most.

For example, during floods, my system can quickly find places where people are seeking help, and urgency can rank these areas. This will help rescue teams act faster and send aid where they need it most, even before official reports come in.

Addressing the challenge

Using social media during disasters will help you, but that’s not always easy. Sometimes people post things that are not true. They also don’t clearly state where the same message is posted multiple times or where the issue lies. This mix can make it difficult for the system to know what’s actually happening.

To fix this, I’m working on how to check A Post reliability. I see who posted it, what words they used, and whether other posts say the same thing.

I also take privacy seriously. I only use posts that anyone can see and do not display names or personal details. Instead, I look at the big picture to find the pattern.

The future of disaster information

As AI systems improve, they could be even more useful during disasters. New tools can help you understand the message more clearly and may help you see where the trouble is coming before it starts.

As extreme weather conditions worsen, authorities need quick ways to get good information. When used correctly, social media can show people where they need them the most. It helps save lives and make supplies faster in the right place.

In the future, I think this will become a regular job in emergencies around the world. My research is still growing, but one thing is clear. Disaster response is no longer about people on the ground, but also about AI systems in the cloud.

This article will be republished from the conversation under a Creative Commons license.