In recent years, we’ve seen a wave of new entrants to the Licence Plate Recognition (LPR) space, particularly through handheld and smartphone-based solutions. On the surface, they look appealing: flexible, and easy to deploy, accessible and incredibly low cost.
In fact, legacy LPR has become so commoditised that some vendors even offer solutions for free as part of a broader enforcement contract.
But, as they say, you get what you pay for.
Legacy LPR systems, including handheld, in-vehicle and on-roof cameras, may tick the box on paper, but in practice, they come with trade-offs that are hard to ignore. And, most critically, draining officer time, creating public friction, and missing the bigger picture of what’s really happening at the curb.
The Hidden Cost of “Free” LPR
Handheld LPR systems are low cost but slow. They typically require officers to manually scroll through 25–30 images per potential infringement to verify a result. With false positive rates hovering around 50%, that’s a significant amount of time wasted chasing errors. Up to 10 minutes per event in many cases.
In an era where enforcement teams are being asked to do more with less, that’s simply unsustainable, and the high error rate doesn’t do the city any favours in the eyes of the citizens, either.
Vehicle-Mounted Systems: Better, But Still Limited
There are other legacy LPR options, of course. One popular choice is vehicle-mounted camera systems or using handheld inside the vehicle. These looks like an improvement in terms of speed and coverage, but they still have a major limitation: they only see in one direction and comes with occlusions.
This matters because infringements can often only be registered by having a true view of a situation. When the view is blocked or obscured by A-pillars or signage, often results in missing violations across the street.
However, what is perhaps even more important is that many of these systems rely on third-party software to interpret LPR data. That makes it difficult to customise, harder to add new scenarios, and plate formats change need to update firmware for accuracy. You’re effectively locked into a fragmented system. It’s one that might look smart, but can’t keep up with the demands of modern enforcement.
In short, these legacy LPR technologies are costing cities by:
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- Wasting Officer Time: Up to 10 minutes per infringement just to verify results
- Damaging Public Confidence: High error rates lead to disputes and distrust
- Missing Key Violations: Limited views miss permit misuse and signage issues
- Locking Teams In: Third-party systems restrict flexibility and slow updates
The SenFORCE Difference: Context is Everything
SenFORCE was built with a different philosophy.
Where legacy LPR systems chase a single image, we capture context. Our solution captures vehicle from multiple angles, environmental data, and scene-specific factors, and these are all stitched together by AI.
This means that the technology empowers enforcement teams to determine whether a true offence has occurred. It produces greater accuracy, faster resolution, and significantly less time spent on manual review.
Importantly, everything, from the AI engine to the hardware, is built and managed in-house. That means that SenSen is not reliant on third-party LPR providers, and continually refine our system based on real-world requirements.
This is what sets SenFORCE apart from older players in the market, including those offering smartphone-based LPR or generic solutions that bolt onto enforcement platforms as an afterthought.
Putting It All Together
Legacy LPR
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- High false positives, heavy manual review
- Single-angle evidence (plate only)
- Limited rule logic (just plate & time)
- Often dependent on third-party LPR
SenFORCE (Context-Aware Enforcement)
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- Accurate, contextual captures, minimal manual intervention
- 180° multimodal imaging, metadata-rich evidence
- Full behavioural analytics and rule engine
- Fully integrated, in-house AI + hardware stack
Why This Matters Now
There’s a growing awareness among enforcement leaders that outdated systems are holding them back. The tools that worked ten years ago, or even five, no longer meet today’s operational pressures.
The move towards contextual, AI-powered enforcement is more than just a technological upgrade. It’s a mindset shift: from reactive to proactive, from labour-intensive to automated, from afterthought to focused.
And while some providers are still patching together legacy components, others are asking better questions: How can we do more with less? What does future-ready enforcement actually look like? How do we make every officer’s time count?
We think those questions are worth exploring, and we’ve built SenFORCE to provide an answer to them.
