Hopes fingerprint tech could trace more criminals
A Sheffield Hallam University-led research team developed AI-powered fingerprint technology that visualizes molecular traces from sweat, potentially increasing usable fingermarks from under 80% to near-full identification. The method, trialed by West Yorkshire Police, reduces processing time from two hours to 15 minutes and can distinguish overlapping prints, including those invisible to traditional techniques.
Researchers at Sheffield Hallam University have developed a new fingerprint technology that captures molecular images of chemical traces left in sweat, improving criminal identification rates. Traditional methods currently allow only under 80% of fingermarks collected by 43 police forces to be used for identification, according to Prof Simona Francese. The AI-driven system analyzes these molecular images within seconds, increasing the potential for evidence recovery. The technology has been tested by West Yorkshire Police, which welcomed the innovation as a tool to strengthen evidence collection and victim protection. It can also process faint or previously invisible prints, reducing analysis time from two hours to 15 minutes. Prof Francese noted that overlapping fingerprints, such as a victim’s and a perpetrator’s, can now be separated more effectively. The project involved collaboration with the University of Bradford, with Prof Hassan Ugail calling it a powerful new resource for law enforcement. The method aims to enhance forensic capabilities by leveraging chemical traces that traditional techniques may miss, offering faster and more accurate criminal identification.
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