GridScout
Vehicle-Mounted Edge-AI Route Intelligence Platform
GridScout is GhostFlight Dynamics’ vehicle-mounted route intelligence platform for offline field collection, roadside detection, GPS/GNSS-linked evidence, review maps, KMZ route packages, and GIS-ready exports.
The platform converts road-facing field collection into structured, location-linked evidence that can be reviewed, mapped, exported, and used to improve AI-assisted infrastructure workflows.
Offline Field Collection | Location-Linked Evidence | Map-Ready Exports | Reduced RF Configuration Options
From Field Collection to Route Intelligence
Roadside infrastructure changes faster than conventional survey workflows can capture it. Signs, hazards, temporary work-zone indicators, route conditions, and infrastructure context may shift between formal mapping cycles, leaving operators and planners with outdated information.
GridScout is designed to close that gap by turning vehicle-mounted field collection into reviewable route intelligence. A route pass captures road-facing evidence, location context, operator status, and AI detections. The completed run can then be preserved, reviewed, exported, and used to improve future model performance through human quality assurance.
The objective is not just to collect raw video. The objective is to produce disciplined field evidence, map-ready outputs, and structured intelligence packages that support faster review, better operational awareness, and repeatable model improvement.
Field-to-Intelligence Workflow
1. Capture
Collect road-facing evidence during a route pass, including video, route tag, operator state, and location context.
2. Detect
Identify roadside objects and route-relevant events at the edge, with detections linked to route and frame context.
3. Preserve
Save the completed field run as a repeatable evidence package with supporting files, status records, logs, and metadata.
4. Post-process
Convert selected runs into review and export products, including map views, evidence packages, KMZ files, and GIS-ready outputs.
5. Improve
Use human QA and validation to refine candidate models, improve weak classes, reduce false positives, and support deployment decisions.
Technical Disclosure & Data Security
This public overview intentionally abstracts specific computers, cameras, internal architecture, model details, and implementation-level components.
Detailed architecture, bill of materials, model notes, data-handling procedures, and implementation-level technical information can be provided under NDA or during pilot scoping.
Security features are designed to protect collected route data through encrypted storage, controlled run authorization, and separation between operational and sensitive data layers.
Request a GridScout Pilot Briefing
Connect with GhostFlight Dynamics to discuss GridScout pilot opportunities, route collection objectives, demonstration constraints, deliverable expectations, data-handling requirements, and operational feedback criteria.