Peer2Park
On-device computer vision

Parking found
in real time.

Your dashcam becomes a parking sensor. On-device AI detects open spots as you drive and shares them before they disappear.

See how it works Why freshness matters
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<60sReport age
94%AI accuracy
~460mH3 precision
20mDedup radius
Spot detected 18s ago near Campus Ave YOLO confidence 94% 3 spaces freed on Main St Community report: Lot B clearing Freshness window: 7 min remaining H3 cell resolution: ~460m Spot detected 18s ago near Campus Ave YOLO confidence 94% 3 spaces freed on Main St Community report: Lot B clearing Freshness window: 7 min remaining H3 cell resolution: ~460m

The problem

Parking apps show you where spots were.

  • × Static maps show theoretical parking, not real availability
  • × Data goes stale in seconds, apps update in minutes
  • × No way to know if a spot is open when you arrive
  • × Drivers circle blocks wasting time and fuel

Peer2Park

Freshness over prediction.

  • ✓ On-device YOLO AI detects spots from live dashcam footage
  • ✓ Crowdsourced reports confirm availability in real time
  • ✓ Spots ranked by recency, not popularity or distance
  • ✓ H3 hex-grid indexing for precise geospatial accuracy

The solution

Built on freshness, not predictions.

On-device AI

YOLO11 and YOLOv26n-OBB run via Core ML. Your camera feed never leaves the device.

Freshness-ranked

Spots sorted by recency, not popularity. The newest signal always surfaces first.

Crowdsourced

Every driver is a sensor. The more people drive, the fresher the data for everyone.

Live capture

See the street through AI eyes.

Real dashcam footage processed by on-device computer vision in real time.

How it works

From drive-by to decision in seconds.

01

Drive captures the street

Your phone's camera passively records as you drive. No hardware, no setup. Just your commute.

02

AI spots the openings

YOLO models run on-device via Core ML, detecting spots with 94% confidence in real time.

03

Nearby drivers decide fast

Fresh detections surface to drivers nearby, ranked by recency. The newer the signal, the better.

Under the hood

Real engineering, not parking promises.

Built on proven ML models, serverless infrastructure, and privacy-first principles.

H3 hexagonal indexing

Resolution-8 cells for geospatial queries and 20m deduplication.

Intelligent navigation

Apple Maps integration with voice search and hands-free guidance.

Privacy-first

All ML on-device. No raw footage shared. Only structured data leaves your phone.

Serverless backend

AWS Lambda, DynamoDB, and API Gateway. Scales with every new driver.

Why freshness matters

Parking data has a half-life measured in seconds.

A spot seen 30 seconds ago is gold. The same spot reported 10 minutes ago is a guess. Peer2Park ranks by recency because curb conditions change faster than any prediction model.

Every report carries a timestamp, a confidence score, and a decay window. You never act on stale data.

11:42:18 — Spot opens A car pulls away near the north entrance. The space is empty.
11:42:31 — AI detects A passing driver's dashcam captures the opening. YOLO inference flags the vacancy.
11:42:39 — Signal shared Detection indexed to H3 cell, surfaced to nearby drivers while still fresh.
11:43:07 — Parked Driver 2 blocks away sees the signal, makes the turn, parks. 49 seconds total.

Join the network

Every driver makes parking smarter.

Turn your commute into shared intelligence. The more people drive, the fresher the data gets for everyone.

Get early access