AI surveillance helps rescue abandoned infant at Halasur Gate

An abandoned infant was rescued within minutes on Tuesday (November 11) morning after the city’s artificial intelligence (AI)-powered surveillance system alerted the Halasur Gate police.

Around 9:35 a.m., a local resident spotted the infant lying abandoned in the Halasur Gate Police Station limits and immediately called ‘Namma 112’. Acting on the alert, the Integrated Command and Control Center (ICCC) used AI and machine learning algorithms to analyse surveillance footage and relayed the information to Hoysala-26 patrol under the jurisdiction of the Halasur Gate police.

Assistant Sub-Inspector Nanjundayya and Assistant Commissioner of Police Shankarlinga Kumar of Hoysala-26 reached the spot within 14 minutes, rescued the infant, and shifted the baby to Vanivilas Hospital for immediate medical attention.

Police have launched a probe and are reviewing CCTV footage using AI-assisted video analytics to trace the person responsible for abandoning the child.

Another incident near Tree Park Metro Station

In another incident, Kadugodi police attended to an early morning altercation between a man and a woman — in which the woman was seriously injured — near Tree Park Metro Station on November 11.

According to officials, around 6:18 a.m., local residents witnessed the duo arguing and contacted ‘Namma 112’. The ICCC analysed the live surveillance footage using AI and machine learning algorithms and dispatched Hoysala-234 patrol under the Kadugodi Police Station limits.

Acting within 12 minutes, Assistant Sub-Inspector Hemala Nayak and Police Commissioner Pundalik of Hoysala-234 reached the spot and gathered details from residents, who informed them that the woman had sustained serious injuries. The locals had already called an ambulance and shifted her to a nearby hospital.

The police team followed up at the hospital, where doctors confirmed that the woman was out of danger and recovering.

Police have launched a search to trace the accused using AI-assisted facial recognition from the metro station and nearby CCTV cameras.