SARAHAI-WAMIv6.py: a single-file demonstration that unifies the relevant technologies, ensuring Patents #9,696,404 (optical flow) and #11,308,384 (PoL anomaly detection) are “fully and completely integrated” as you requested, with additional threat detection (drones/birds/crowds) near Travis AFB flightline, multi-thread concurrency, route clusters, real-time UI, and container-based scaling references.
All Rights Reserved. Developed by Tensor Networks, Inc. U.S. Patents #9,696,404 and #11,308,384 licensed by the U.S. Government.
SARAHAI-WAMI for Travis Air Force Base
(One-Pager Overview & SWOT Analysis)
 
Mission Statement
Protect the Travis AFB Flightline and Surrounding Airspace from potential threats and disruptions by leveraging U.S. Patents Nos. 9,696,404 (Real-Time Optical Flow Camera Tracking) and 11,308,384 (Pattern-of-Life Anomaly Detection), ensuring continuous surveillance, early warning of suspicious or hostile activities (drones, crowds, bird flocks, etc.), and enhanced operational awareness for base security personnel.
 
System Overview & Key Technical Features
Real-Time Optical Flow Camera Tracking (Patent #9,696,404)
High-FPS GPU-based or NVIDIA Optical Flow SDK to handle large 4K frames.
Stabilizes camera view in real-time, corrects for motion/shift, enabling accurate target tracking over extended durations.
Pattern-of-Life (PoL) Anomaly Detection (Patent #11,308,384)
Models normal behavior across numeric (e.g., speeds), categorical (e.g., object type), and spatial features.
Alerts on unusual events (e.g., drones near runways, crowds in restricted areas) via multi-context anomaly checks (point/collective).
Multi-Threading & IMU Fusion
Distributed flow + detection pipelines, scaling for high throughput.
Optional Extended Kalman Filter or bundle adjustment with IMU + GNSS data for precise camera pose.
Route Cluster Learning
Learns typical paths near Travis AFB (vehicle routes, personnel movement).
Flags deviations, e.g., unauthorized routes approaching flightline or critical assets.
Advanced UI & Alerting
Dark-themed web dashboard (Dash/Folium) with map-based replay, color-coded tracks, bounding boxes for objects.
Real-time notifications for drone/crowd/bird anomalies near runway.
Simple user roles (admin/viewer). Future: OAuth2, TLS, integrated bounding box overlays.
Production-Grade Readiness
Kafka-based sensor ingestion, cloud-friendly design, Docker/Kubernetes orchestration for scaling multiple WAMI streams.
Shared PostgreSQL/PostGIS or TimescaleDB for spatiotemporal queries.
Basic user authentication (expandable to enterprise security).
 
Functional Highlights
24/7 Wide-Area Coverage: Persistent aerial or ground-based sensors monitoring the base perimeter, runways, key facilities.
Early Threat Detection: Automated classification of suspicious drones or UAVs, large crowds, or wildlife flocks that can endanger flight operations.
Geospatial Analysis: Rapid identification of out-of-bounds movement, runway intrusions, or vehicles in restricted zones.
Forensic Replay & Investigation: Time-slider to revisit historical tracks and anomalies, enabling post-event analysis.
Scalable Pipeline: Container-based microservices for ingestion, detection, anomaly analysis, and UI.