Real-Time AI Filtering
Intelligent algorithms scan images to flag potential violations, instantly deleting the vast majority of data where no offence occurs. Human Verification (in Sussex Police, to date) Flagged images are anonymised and reviewed by at least two trained human assessors before being passed to police staff for final confirmation. Offences & Fines (in Sussex Police, to date) Confirmed violators face standard UK penalties, such as a £200 fine and 6 penalty points for handheld mobile use, or educational courses/fines for seatbelt omissions. Privacy Controls (in Sussex Police, to date) Systems are programmed to ignore non-relevant data and do not use facial recognition software.
This is outstanding police work. Commander Neerav Patel and his team have driven neighbourhood crime down 14% in 12 months, 35,000 fewer reported offences. Theft from the person down 23%. Robbery down 11%.
But I keep coming back to the same question. What if the bike never made it to the road in the first place? The dyno tells you what the bike can do after it's been modified and ridden. A permission layer tells the bike what it's authorised to do before it activates. Verified identity. Verified compliance. Verified authorisation. Before the first wheel turn. Not instead of enforcement. Upstream of it. That's the layer that changes the scale of this problem permanently. 35,000 fewer crimes is remarkable. Imagine what zero illegal activations looks like? That's what 'Tevver' is building, says Stuart Riddick, its CEO.  Click image for full summary Some manufacturers are starting to look at enticing the few remaining manual car buyers to move away from liquid propulsion but retain the feeling of driving a car where YOU decide how to apply the power to the wheels. The best of "both worlds"?
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