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Case Study:

Identifying Missing Victims with AI-powered Solutions

When wildfires broke out in a region after a 3-year long drought, nearly two million hectares were burned to the ground. Several thousand public and private buildings as well as communication lines were destroyed within hours. The wild fires were very dynamic, quickly changing course due to strong winds. This unpredictability made it even harder for the regional crisis center to follow up on the missing person reports that kept flooding in.


The regional authorities were looking for various platforms and solutions to find a way to quickly and efficiently locate missing persons, ideally in real-time, for evacuation. Because wildfires were moving rapidly and unpredictably, the regional crisis center needed a way to receive up-to-the-minute information about the identification and whereabouts of missing persons. Since the regional crisis center was staffed by a mix of emergency response personnel operating under tremendous pressure, an automated solution was the preferred option. The Regional Council reached out to Cobwebs to provide the regional crisis center with a user-friendly solution to identify and locate missing victims quickly and efficiently without draining resources.

Almost all residents in the affected region were using the internet and social media to stay in touch. They were posting on social media, forums and message boards, taking and posting selfies, and leaving comments to reach out to relatives, friends, neighbors, and the authorities. Tracing these digital footprints was the key to finding the missing persons. Using natural language (NL) processing and automated artificial intelligence (AI) tools, our WEBINT platform automatically scanned social platforms and other publicly-accessible data using keywords. The platform also revealed the relevant locations that the missing victim was associated with by identifying places mentioned on social media.


The AI-powered WEBINT solution made it possible to extract and analyze victim-related data derived from their digital footprint and online presence. Using criteria such as relevant areas and keywords associated with the wild fires, the AI-powered platform revealed and analyzed location-based data and displayed the results in real-time on interactive maps in the platform’s GUI. This allowed the staff at the regional crisis center to find and rescue wild fire victims that were reported missing. Rescue workers were dispatched to the pinpointed locations to take care of the identified victims. Since wild fires are a recurring phenomenon in this region, our platform will show its mettle now and in the future.


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