Full roadside tolling without cutting the pavement.
Tollscopic is an AI-native RTCS for all-electronic tolling: gantry-mounted sensing, trajectory-based event correlation, multi-sensor classification, immutable evidence, and clean integration with the back office already in place.
Roadside tolling has accumulated devices faster than it has changed architecture.
Cameras, RFID readers, axle sensors, LiDAR, and lane controllers all observe the same traffic stream, but many systems still depend on event timing and device-specific chains to decide which signals belong together. That works until a real road gets messy.
Stop-and-go flow. Trucks blocking camera views. Vehicles straddling lanes. Missing reads. Curved geometry. Sensors that disagree. The result is not just a missed read. It is a transaction with weak provenance, an exception that requires manual review, or a system that cannot improve without changing the roadside again.
Four layers. Evidence is the stable one.
Each roadside device produces evidence. Edge compute turns video into vehicle trajectories. The cloud transaction layer binds evidence to those trajectories, fuses classification signals, and builds the transaction record. A back-office interface publishes that record without making the roadside logic dependent on one billing platform.
Gantry-mounted cameras, RFID, classification sensors, LiDAR where configured. Every device produces evidence.
Edge compute turns sidefire and wide-angle video into a vehicle trajectory through the zone.
Evidence binds to the trajectory. Classification is fused with confidence and provenance. The transaction is assembled.
Transactions publish through a stable adapter to the operator's BOS / OBO. The immutable evidence store remains available for replay.
The advantage is not a single sensor. It is how the system treats every sensor as evidence and every vehicle as a tracked object.
That gives the platform a better way to handle ambiguity, a stronger basis for audit, and a more flexible path for modernization.
The overview is a map. Each technical page picks up where this one stops.
What gets mounted and why gantry-only matters.
How evidence becomes a toll transaction. The strongest diagram in the section.
DVAS and immutable evidence behind every transaction.
How Tollscopic monitors, tests, releases, and improves.
Why this architecture changes the legacy tolling equation.
Real roadside constraints have shaped the product.
The story below is about engineering conditions, not market footprint. Each condition is a technical lesson the system has had to absorb.
Overlapping vehicles and dense evidence streams
Off-axis camera views and lane ambiguity
Wind, salt, and difficult maintenance access
Degraded WAN handled with local buffering
Bring us the toll zone, the constraints, and the back office.
Tollscopic is strongest where the old architecture is becoming the bottleneck: dense traffic, brittle lane hardware, opaque audit, and systems that cannot improve without major roadside change.