Completed Engineering Computing & AI

ISIS - An Integrated Sensor Information System for Crime Prevention

In plain English

AI plain-English summary

A bus or train can scan every passenger for explosives, weapons, and known criminals before they board, using a network of cameras, microphones, and radio-frequency sensors. This matters because public transport is a soft target. Current security relies on visible patrols and CCTV that only records after an incident. ISIS—the Integrated Sensor Information System for Crime Prevention—aims to detect threats in real time, as they enter the vehicle. It combines three sensing methods: video cameras and audio microphones for facial and voice recognition against watchlists, plus radio-frequency and microwave sensors to scan for hidden electronics, such as detonators concealed inside laptops or mobile phones, or explosive devices placed under a bus or train. If successful, the system would alert security and transport staff the moment a threat is identified, and manage its own network of sensors. This could shift public transport security from passive recording to active, automated threat detection. The technology might eventually extend to other crowded, vulnerable spaces—stations, airports, or stadiums—where screening every person and bag is currently impractical.

View original technical description
ISIS will detect threats on public transport, inform key decision makes of that threat and manage its own network. It will use video cameras, audio microphones and RF/microwave sensors to detect threats as they enter buses or trains. ISIS will use template matching to use the video and audio streams to identify known criminals or terrorists and alert security and transport staff. In cases were the passenger is unknown it will use advanced RF scanning techniques to check for external intrusion into the vehicle space such as an explosive device placed under a bus or train and will also check to unknown electronics used as detonation mechanisms for explosives concealed insit a laptop or mobile phone.

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Researchers

Darryl Stewart (Co-Investigator)David Linton (Principal Investigator)Ian O'Neill (Co-Investigator)Paul Miller (Co-Investigator)Sakir Sezer (Co-Investigator)Vincent Fusco (Co-Investigator)

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Original classification

Research Grant

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