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Transform your existing traffic camera infrastructure into an intelligent enforcement system. Visylix automatically detects red-light running, speeding, wrong-way driving, and illegal parking with court-admissible evidence generation and real-time alerting.
Key challenges that organizations face without intelligent AI-powered solutions.
Manual traffic monitoring cannot scale across thousands of intersections and road segments, leading to inconsistent enforcement coverage and high labor costs.
Traditional enforcement relies on officer presence, missing the majority of violations that occur outside patrol routes and peak enforcement windows.
Generating legally admissible evidence for each violation requires precise timestamps, high-resolution imagery, and license plate capture that manual processes struggle to deliver consistently.
Legacy fixed-function traffic cameras lack the intelligence to classify violation types, adapt to changing conditions, or integrate with modern e-challan and citation management systems.
Intelligent capabilities that transform your existing camera infrastructure into a powerful decision-making engine.
Simultaneously detects red-light running, illegal U-turns, wrong-way driving, stop-sign violations, and lane discipline infractions from a single camera feed using deep learning models trained on diverse traffic scenarios.
High-accuracy ANPR captures plate numbers across multiple vehicle types and lighting conditions, automatically linking detected violations to vehicle registration data for streamlined citation processing.
Automatically compiles timestamped video clips, high-resolution snapshots, speed estimates, and violation classification metadata into court-admissible digital evidence packages for each detected infraction.
Centralized command center interface delivers instant violation alerts with location mapping, trend analytics, and hotspot identification to help traffic authorities prioritize enforcement resources effectively.
Quantifiable improvements delivered through AI-powered intelligence and automation.
AI captures violations around the clock with near-perfect accuracy, far exceeding manual enforcement coverage.
Automated detection and evidence generation dramatically reduce the manpower required for traffic enforcement operations.
Faster processing from violation detection to citation issuance through automated evidence compilation and plate recognition.
Consistent AI enforcement at high-risk intersections creates measurable deterrence and improves overall road safety outcomes.
Speed estimation, line crossing for lane and signal violations, direction of travel for wrong-way detection, and ANPR for plate capture. Speed requires a calibration of at least four points per camera; without calibration the model produces no output rather than an unreliable one.
That is a legal question for your jurisdiction, not a product claim. Visylix provides the supporting controls: SHA-256 hashing, evidence lock that prevents retention rules deleting a recording, and a full audit trail of who accessed or exported it. Whether that satisfies your evidentiary standard is for your legal team.
It depends on calibration quality, camera geometry and distance, so it is validated on your own installation during the proof of concept. Visylix publishes no speed accuracy figure because none has been measured against a reference. Visylix publishes no model accuracy figures at all; every model is validated on your own footage instead.
Yes, by plate. Plate journeys are exact and assemble the same plate read at different cameras into one timeline with travel times between points, which also yields average speed over a section.
Usually. ONVIF discovery and RTSP cover most IP cameras, and GB28181 covers equipment built to the Chinese national standard common in some municipal deployments. ANPR quality still depends on camera placement, angle and shutter speed.
See how Visylix AI can automate traffic violation enforcement across your city's camera network with real-time detection, evidence generation, and actionable analytics.