Roads
Disconnected signal + camera networks
Congestion data sits in one tool · cameras in another · re-routing happens manually after delays.
- Cameras siloed from CAD
- Manual diversion plans
- Late incident impact
A connected mobility command layer for roads, transit, parking, EV chargers and future autonomous corridors. Reduce congestion, improve service reliability, increase infrastructure uptime — with one real-time operating view.
Congestion data sits in one tool · cameras in another · re-routing happens manually after delays.
No live picture of station crowding, route delays or passenger flow — riders get stuck, operators are blind.
Field teams discover faults from complaints — not from sensor data.
Real-time heatmaps, incident impact, signal coordination + AI re-route advisor with cited reasoning.
Bus, metro, tram or shuttle status, route delays, station crowding and passenger flow on one canvas.
Live charger health, demand hotspots, queue time. Roadside units and AV corridors mapped + monitored.
Each surface runs on the same event model, the same map and the same audit trail — so a signal change, a bus delay and a charger fault are the same kind of object.
| Surface | What it ingests | What operators do | Typical scale |
|---|---|---|---|
| Roads & signals | Loop counters, radar, ANPR, adaptive controllers, CCTV analytics | Retime corridors, push diversions, close lanes with a workflow | 400–2,000 intersections |
| Transit | AVL/GPS, APC passenger counts, GTFS-RT, depot telematics | Hold, short-turn, add capacity, notify riders | 10–400 vehicles per mode |
| Parking | Bay sensors, barrier counts, payment systems, kerb permits | Dynamic pricing, guidance signage, enforcement tasking | 3k–60k stalls |
| EV charging | OCPP 1.6/2.0.1 telemetry, fault codes, session records | Dispatch maintenance, rebalance load, publish availability | 50–5,000 points |
| Autonomous corridors | Roadside units, V2X, lidar zones, HD-map deltas | Certify corridors, geofence, monitor disengagements | Pilot → citywide |
A collision on 5th & Park, from detection to cleared lane — every step time-stamped and attributable.
Radar flags a speed collapse; the nearest camera confirms it on a vision score, so no operator has to go looking.
The platform scores severity from lane blockage, queue growth and downstream demand, then drafts a diversion.
Operator approves once. Signals retime, signage updates, EMS is dispatched and transit is told to hold.
NTCIP 1202/1203 signal controllers, TMDD centre-to-centre, SPaT/MAP broadcast, Datex II feeds.
GTFS and GTFS-Realtime in and out, SIRI feeds, depot and AVL telematics, fare-system events.
OCPP 1.6J and 2.0.1, OCPI roaming, CDS kerb data specification for permits and loading zones.
Traffic control is a public-safety function. Nothing acts on the street without a policy behind it and a name against it.
| Control | How it works |
|---|---|
| Human-in-the-loop by default | AI proposes; a named operator approves. Auto-execution is opt-in per action type and per corridor. |
| Policy guardrails | Diversions cannot route heavy vehicles onto residential streets or past a school in restricted hours. |
| Full audit trail | Every proposal, approval, rejection and signal change is written immutably with the evidence that triggered it. |
| Explainability | Each recommendation cites the sensors, thresholds and prior incidents it was derived from. |
| Privacy | ANPR and video are processed for counts and classification; identity data is not retained by the mobility layer. |
A walkthrough with our solutions team — your data, your departments, your workflows.