# DAARS Instruments | TurnProof

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Dhananjay Sharma](https://cerebralvalley.ai/u/DAARS)
- **GitHub:** https://github.com/daarsai/daars_turnproof
- **Demo video:** https://youtu.be/ZzDE0EvqH0c
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/893

TurnProof — verifiable evidence for aircraft turnaround delay claims

When an aircraft departs late, the airline attributes delay minutes to its ground handler, at a contractual rate per minute. The airline’s claim, the handler’s milestone log and the stand-camera footage frequently disagree, and today resolving that means manual CCTV review and negotiated minutes. TurnProof, by DAARS Instruments, turns one stand-camera clip, the airline’s claim and the handler’s log into a human-reviewed, cryptographically verifiable evidence packet that both parties can check independently.

How it works. SAM 3.1 is prompted on the whole video with three nouns — aircraft, vehicle, person — so no equipment-specific detector is needed. Hold zones are defined as fractions of SAM’s aircraft box, so they move with the aircraft and need no pixel calibration. A deterministic occupancy rule in real seconds (docked ≥ 1 min, then away ≥ 1 min, scaled by the clip’s declared speed factor) derives loader_docked_start → loading_complete. Muse Spark 1.3 extracts structured claims from airline MVT/DLA telex, email or report photos, cross-checked by a deterministic parser and confirmed by the operator; it also returns strict-JSON keyframe facts that can flag a candidate event but never decide it. The rule alone compares milestones against the claim window and computes supported minutes. The handler confirms, rejects or corrects; the airline verifies, acknowledges or disputes.

Evidence integrity. Every frame is SHA-256 hashed before processing and encrypted at rest; persons are blurred from SAM’s person boxes before display. Packets are canonical JSON → SHA-256 → Ed25519, anchored in a hash-chained event log. A standalone verify_packet.py (standard library + cryptography) runs seven checks with no TurnProof code and no API key; a tamper test shows failure on a single flipped pixel. The repository ships the demo’s real packets in examples/.

Demo. Three synthetic claims on licensed footage: a 3-minute claim the video supports in full although the handler’s own log said otherwise; a 12-minute claim the video supports for only 2, with an airline dispute and a handler response; and footage that cannot establish the event, where TurnProof returns “cannot be determined” rather than a verdict.

Production path. The pipeline, packet format, verifier, event library (loading validated; fuelling and catering defined and labelled unvalidated), RTSP/ONVIF recorder with on-block → off-block scheduling, AODB feed, ADS-B adapter, claim intake and HMAC-signed webhooks are already in pilot shape. v0.1 deliberately keeps runs as folders, SQLite per run, threaded jobs and a role toggle; a pilot swaps those for object storage, Postgres, a queue and tenant logins without touching a model or the packet. Model responses are cached per clip and each run reports its own cost.

Limits are stated plainly in the repository: three time-lapse clips, estimated speed factors, one validated event type, no accuracy claim.

Every minute claimed deserves evidence.

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