[ Body-Cam ]
Edge Capture and Local Review System Concept
Executive Summary
Body-Cam is a concept track focused on resilient field capture in low-connectivity environments. The direction prioritizes reliable evidence collection, local processing, and secure synchronization.
The goal is practical: reduce data-loss risk during field operations and create a clean chain from capture to review without depending on continuous cloud connectivity.
Reference Hardware Architecture
Field Capture Unit
- Capture: wearable camera module for timestamped media recording.
- Storage: encrypted local storage for offline-first retention.
- Telemetry: low-bandwidth status signaling for operational visibility.
- Power: replaceable battery architecture for longer shifts.
Local Review Station
- Compute: edge processing node for media indexing and triage.
- Sync: short-range secure transfer for field uploads.
- Control: operator console for review and export workflows.
Intelligence Layer (Concept)
This concept focuses on practical automation around indexing, summarization, and retrieval rather than sensitive operational features.
- Event Summarization: generate lightweight event metadata from captured media for quick operator triage.
- Sync Orchestration: coordinate offline capture and scheduled secure upload windows.
- Local Model Review: run classification and tagging tasks on local compute where feasible.
- Data Integrity: maintain timestamped records and retention controls for auditable workflows.
Operational Flow
1. Field Capture
Media and event markers are captured locally with basic status telemetry.
2. Secure Sync
When connectivity is available, files are transferred to a controlled local station for indexing.
3. Review & Retention
Operators review summaries, verify critical events, and apply retention policy for storage and exports.
Potential Applications
- Industrial Safety: incident documentation in plants and remote field sites.
- Infrastructure Inspection: structured visual logs for maintenance and compliance workflows.
- Field Research: offline-first data capture for teams working in weak-connectivity environments.