Facial recognition leads to arrest of over 170 suspects in Essex

Latest arrests include theft and assault offenders

Author: Ellie RobsonPublished 16th Jul 2026

Essex Police have utilised Live Facial Recognition (LFR) technology to make more than 170 arrests so far, with nine resulting from June alone.

The use of this technology has helped police with various offences, particularly assault and theft, and has also acted as a deterrent to crime and disorder in the area.

Detective Superintendent Stephen Jennings emphasised the continual value of LFR technology in locating suspects.

“It allows officers to progress investigations and get justice a step closer for victims,” Jennings said.

He explained that during recent deployments, individuals visibly avoiding cameras and officers have been identified as wanted for other offences, leading to arrests for crimes such as burglary.

A watchlist is generated before each deployment, containing images and data of individuals the police are seeking, including those wanted for a crime or subject to court orders, posing a risk to the public, or being vulnerable.

Only those on the watchlist can be matched, and when a possible match is found, an alert is generated.

Jennings assured the technology’s accuracy, stating there's never been an arrest due to a false positive alert during deployments, even if a face isn't fully visible due to a covering.

If an individual isn’t on the watchlist, their image is deleted almost instantly and isn't stored.

Jennings indicated arrests in May showcase LFR’s value:

“Police officers spend a significant amount of time trying to locate individuals who are either wanted for criminal offences or at risk of harm."

He elaborated that LFR allows this process to be more efficient, permitting officers to focus on visible policing and community engagement.

In comparison, Jennings said, having an officer manually identify 1,000 individuals sought by police on a busy high street would be impractical, whereas LFR accomplishes this task quickly and reliably.

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