Passenger
Passenger analytics
Track boardings and drop-offs by location, monitor passenger presence, and compare ridership against tickets sold for better visibility and control.
Stop fleet accidents before they happen
AIVAT Safe Driving uses edge AI to detect driver risk, road hazards, and unsafe behaviors in real time — helping fleets respond faster and operate more safely.
- On-vehicle edge AI
- 25+ real-time detections
- In-cabin & dashboard alerts
- Works offline by design
The road risk visibility gap
Most fleet accidents are preventable.
Risks are detected too late.
Driver distraction, drowsiness, cellphone use, unsafe following distance, and road hazards often appear seconds before an accident. But many traditional systems depend on cloud connectivity, delayed review, or manual follow-up. AIVAT Safe Driving processes events directly on the vehicle to help fleets detect risk earlier and respond faster.
24/7
On-vehicle AI monitoring
25+
Real-time detections
Edge-native
Works offline by design
<250 ms
Alerts triggered in real time
Driver + road
Cabin and forward-facing risk detection
The shift
From basic dashcam AI to prevention-grade fleet safety
Traditional dashcam AI helps review incidents. AIVAT Safe Driving is built to help prevent them.
Legacy
Traditional dashcam AI
AIVAT Safe Driving
Prevention-first
Review only
Live preventionAIVAT prevents what legacy reviews
Basic alerts
Limited context and delayed insights
Real-time on-vehicle alerts
Instant, actionable alerts in the moment
Narrow feature set
Focused on review, not prevention
Broader coverage
Monitor more of the driver, vehicle and road
Reactive workflows
Incidents are discovered after they happen
Near-miss detection
Catch risky behavior before it escalates
Not covered
Higher precision
AI models trained for real-world driving
Use cases
Every risk on the road, watched in real time
Two cameras feed the AIVAT edge unit — one inside the cabin, one facing the road. Each runs its own catalog of real-time detections.
Cabin camera
Driver monitoring and behavior
Detects drowsiness, distraction, phone use, smoking, and seatbelt compliance in real time.
Drowsiness and fatigue
Continuously analyze eye closure ratio, blink rate, head pose, and yawn cadence to surface fatigue before it becomes a crash. Drivers receive in-cabin audible alerts; supervisors get an event with video evidence.
- Yawn & micro-sleep detection
- In-cabin audible alert
- Coachable evidence clips
Front camera
Road risk and hazard detection
Identifies lane drift, tailgating, hard braking, collision risk, and environmental hazards as they develop.
Collision and spacing warning
Continuously estimate time-to-collision against vehicles, cyclists, and pedestrians ahead.
- Time-to-collision estimation
- Vehicle, cyclist, pedestrian classes
- <50 ms edge-to-alert latency
- Severity-tiered escalation
Architecture
Processing happens on the vehicle
All detection runs on the AIVAT edge processing unit installed in your vehicles. No cloud dependency. No latency. No privacy compromise.
01Vehicle inputs
Cabin camera
Driver-facing IR-capable camera for behavior & state
Road camera
Forward-facing for collision risk, lane, and hazards
Telemetry & GPS
Speed, heading, harsh-event signals fused with vision
Wearables (optional)
Heart-rate / HRV signals for fatigue corroboration
Plug into existing fleet hardware
02AIVAT edge Unit
On-vehicle inference
A ruggedized edge unit runs every model locally. Alerts fire whether the vehicle is in a tunnel, a depot, or a cellular dead zone.
On-vehicle inferenceOffline-capablePer-fleet calibration
03Outputs & response
In-cabin audible alert
Driver hears the warning before the supervisor does
Dashboard event
Supervisor sees clip, severity, location, score
Email & WhatsApp escalation
Auto-route by severity, route, or driver tier
Fleet analytics
Driver scoring, trip risk index, coaching loop
Dashboard
Turn every event into a safer next trip
Alerts go to the cabin and the dashboard the moment they fire. Then the platform turns them into driver scores, coaching playlists, and audit-ready evidence — closing the loop between detection and behavior change.
Driver risk score
Per-trip and per-driver index updated from every event.
Coaching loop
Auto-bundle clips into weekly coaching playlists per driver.
Evidence clips
Every alert ships with the triggering video and frame.
Audit trail
Tamper-evident event history for insurance and compliance.
Optional modules
Add the modules your fleet needs
Extend AIVAT Safe Driving with passenger analytics, pre-trip validation, biometrics, and compliance integrations.
Health
Pre-trip authorization
Automate Romberg-based balance validation before departure to help confirm drivers are fit to operate and reduce preventable risk before the trip begins.
Biometrics
Wearable integration
Connect assigned smart wearables to monitor biometric signals such as sleep quality, oxygen saturation, heart rate, and other driver wellness indicators that support early risk detection.
Compliance
Safety validation integration
Integrate breathalyzers and blood pressure monitoring stations into pre-trip workflows to help verify driver readiness and reinforce compliance before dispatch.
Performance
Performance built for demanding fleet operations
AIVAT Safe Driving delivers fast on-vehicle intelligence, reliable offline alerting, and deployment readiness across multiple fleet environments.
Detections
25+
Real-time detections covering driver, road, and vehicle state.
Edge-to-alert latency
<50ms
On-vehicle
100%
Processing runs on the edge — no cloud dependency, no privacy exposure.
3 sectors deployment-ready
Proven across cargo, logistics, and passenger transport fleets.
Edge-first architecture
Core intelligence runs on the vehicle for resilience and privacy.
Reliable in the field
Built for real-world fleets, even where connectivity is inconsistent.
Ready to make every trip safer?
Deploy AIVAT Safe Driving across your fleet — pilot in weeks, scale to thousands of vehicles. Edge AI, real-time alerts, no cloud dependency.