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Bengaluru Man Says AI Mistook His Guitar for Passenger in Helmetless Challan
Police said the system misread a guitar case as a pillion rider and sent the false challan to the scooter owner’s wife.
- On Saturday, September 26, 2026, an AI traffic camera in Bengaluru mistakenly issued a helmet violation fine to Souvik Dutta, identifying his guitar case as a passenger traveling from Hebbal toward Tin Factory.
- Dutta raised a complaint on the Bengaluru Traffic Police handle, stating, "I was riding my wife's two-wheeler alone with my guitar slung on my back in Bangalore," challenging the "Pillion riding without helmet" violation.
- A senior police officer admitted the system occasionally misidentifies objects, noting it even flags a small child sitting between two people, and conceded the technology has yet to achieve 100% accuracy.
- Responding to the post, BTP officials instructed Dutta to contact the traffic automation section for rectification, noting violations can be questioned and verified by a dedicated team.
- Many motorists have raised concerns on social media about AI-based enforcement cameras, claiming they unfairly book drivers for stopping on zebra crossings, reflecting broader limitations of automated traffic detection systems.
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Bengaluru Man Fined INR 500 As AI Traffic Camera Mistakes His Guitar for Helmetless Pillion Rider | 📰 LatestLY
A Bengaluru man has claimed that an AI powered traffic camera fined him INR 500 after mistaking the guitar strapped to his back for a pillion rider without a helmet, sparking a viral debate on X over the accuracy of automated traffic violation detection systems used by Bengaluru Traffic Police. 📰 Bengaluru Man Fined INR 500 As AI Traffic Camera Mistakes His Guitar for Helmetless Pillion Rider.
·Mumbai, India
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In Bengaluru, an AI traffic camera mistook a guitar slung over a biker's back for a human. The camera mistook it for a helmetless pillion rider and issued a 500-rupee fine. The rider shared the incident on social media, and this bizarre AI error went viral.
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Total News Sources12
Leaning Left2Leaning Right4Center1Last UpdatedBias Distribution57% Right
Bias Distribution
- 57% of the sources lean Right
57% Right
L 29%
14%
R 57%
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