.jpg)
Amusing AI Camera Blunder in Bengaluru! ?500 Fine for Not Wearing a Helmet—Because the Guitar on the Back Was Mistaken for a Person
Bengaluru: An AI traffic camera in Bengaluru made a bizarre error. It mistook a guitar strapped to a two-wheeler rider's back for a pillion rider and issued an e-challan of ?500 for not wearing a helmet.
A citizen named Souvik Datta was riding his wife's scooter along the Outer Ring Road with a guitar bag strapped to his back. He was wearing a helmet, and there was no other person on the scooter. On September 15, the AI ??camera captured a photo of the scooter; it identified the guitar as a 'pillion rider' and sent a ?500 fine directly to his wife's mobile phone.
Souvik Datta was astonished when he saw the challan and the photo the next day. The photo clearly showed him wearing a helmet, with only the guitar visible behind him. He shared the challan and the photo on social media, questioning the 'smart' system. After the post went viral, users responded with amusement and mocked the AI ??system.
Following this incident, the Bengaluru Traffic Police issued an official response. They have initiated the process to cancel the erroneous challan and have urged the affected individuals to email automationpubbcp@ksp.gov.in or contact the control room.
Under the AI ??surveillance system implemented by the Bengaluru Traffic Police in December 2022, fines are levied automatically without human verification of the photographs. This incident has once again highlighted the flaws in the automated system.
Bengaluru: An AI traffic camera in Bengaluru made a bizarre error. It mistook a guitar strapped to a two-wheeler rider's back for a pillion rider and issued an e-challan of ?500 for not wearing a helmet.
A citizen named Souvik Datta was riding his wife's scooter along the Outer Ring Road with a guitar bag strapped to his back. He was wearing a helmet, and there was no other person on the scooter. On September 15, the AI ??camera captured a photo of the scooter; it identified the guitar as a 'pillion rider' and sent a ?500 fine directly to his wife's mobile phone.
Souvik Datta was astonished when he saw the challan and the photo the next day. The photo clearly showed him wearing a helmet, with only the guitar visible behind him. He shared the challan and the photo on social media, questioning the 'smart' system. After the post went viral, users responded with amusement and mocked the AI ??system.
Following this incident, the Bengaluru Traffic Police issued an official response. They have initiated the process to cancel the erroneous challan and have urged the affected individuals to email automationpubbcp@ksp.gov.in or contact the control room.
Under the AI ??surveillance system implemented by the Bengaluru Traffic Police in December 2022, fines are levied automatically without human verification of the photographs. This incident has once again highlighted the flaws in the automated system.
A citizen named Souvik Datta was riding his wife's scooter along the Outer Ring Road with a guitar bag strapped to his back. He was wearing a helmet, and there was no other person on the scooter. On September 15, the AI ??camera captured a photo of the scooter; it identified the guitar as a 'pillion rider' and sent a ?500 fine directly to his wife's mobile phone.
Souvik Datta was astonished when he saw the challan and the photo the next day. The photo clearly showed him wearing a helmet, with only the guitar visible behind him. He shared the challan and the photo on social media, questioning the 'smart' system. After the post went viral, users responded with amusement and mocked the AI ??system.
Following this incident, the Bengaluru Traffic Police issued an official response. They have initiated the process to cancel the erroneous challan and have urged the affected individuals to email automationpubbcp@ksp.gov.in or contact the control room.
Under the AI ??surveillance system implemented by the Bengaluru Traffic Police in December 2022, fines are levied automatically without human verification of the photographs. This incident has once again highlighted the flaws in the automated system.
