top of page
Group 1000002298 (1).png

King Salman Bin Abdulaziz Royal Reserve

  • Oct 31, 2025
  • 3 min read

AI-Powered Wildlife & Intrusion Monitoring built with United Defense through the L19 AI Lab


Protecting biodiversity at national scale requires more than patrol means. It requires persistent visibility, fast decision-making, and systems that work under real operational constraints.


To meet this challenge, the King Salman Bin Abdulaziz Royal Reserve partnered with United Defense and the L19 AI Lab to deploy a mission-ready Wildlife Detection and Tracking Platform that brings AI, drones, and GIS into a single operational intelligence layer.


Rugged mountains at the King Salman Bin Abdulaziz Royal Natural Reserve north of the Kingdom. Source: Saudipedia
Rugged mountains at the King Salman Bin Abdulaziz Royal Natural Reserve north of the Kingdom. Source: Saudipedia


Customer Context


The King Salman Bin Abdulaziz Royal Reserve is one of Saudi Arabia’s most strategically important protected natural areas, responsible for both wildlife conservation and reserve security across vast and remote desert terrain. The operating environment is defined by scale, harsh conditions, and strict governance requirements.


  • Operates across expansive desert zones with limited physical accessibility

  • Mandated to protect endangered species, monitor biodiversity, and prevent poaching

  • Requires strict data sovereignty, on-prem deployment, and human-in-control operations

  • Relies on long-endurance drone platforms and GIS-based command workflows


This context ruled out cloud-dependent tools or black-box autonomy, demanding a system that could be trusted operationally and governed locally.


The Operational Problem


Despite the use of drones and ranger patrols, the Reserve lacked a unified, real-time operational picture. Surveillance and response workflows were constrained by manual processes and fragmented systems.


  • No continuous, real-time visibility into wildlife movement patterns

  • Delayed or missed detection of unauthorized humans or vehicles

  • Heavy reliance on manual patrols with limited persistence

  • Disconnected data between drones, rangers, command centers, and GIS platforms

  • Intermittent connectivity and environmental stress from heat, dust, and low visibility

  • A strict requirement that AI assist operators, without autonomous control of flight or targeting


What was missing was an intelligence layer capable of turning drone feeds into actionable, operator-validated insight.


The L19 AI Lab Solution


Working closely with our sister company, United Defense, our L19 AI Lab designed and deployed a Wildlife Detection & Tracking Platform purpose-built for conservation and security missions under real operational constraints.


  • Real-time AI detection, classification, and multi-object tracking of wildlife, humans, and vehicles from EO and IR drone feeds

  • Assistive Target Tracking (Active Lock), where AI provides visual guidance, geolocation, and tracking continuity while operators authorize every maneuver

  • High-accuracy Video-to-GIS localization (≤5m CEP) using RTK GNSS and laser rangefinder fusion

  • Automated intrusion alerting with prioritization, de-duplication, and operator validation

  • Native GIS integration publishing live detections, tracks, and heatmaps directly into ArcGIS dashboards

  • Fully on-prem deployment as a code-signed Windows service, ensuring data sovereignty and security

  • Offline buffering and automatic backfill to guarantee zero data loss during network interruptions


The system was integrated with United Defense UD-530 and UD-555 long-endurance drone platforms, deployed across on-prem ground stations, and designed to operate reliably across day, night, dusk, and dawn in desert conditions.


United Defense UD-555 Al'AARIDH Technical Specifications
United Defense UD-555 Al'AARIDH Technical Specifications

Operational Impact


Once deployed, the platform fundamentally changed how the Reserve monitors, protects, and responds across its territory.


  • Continuous, real-time visibility into wildlife presence and movement

  • Intrusion detection reduced to under one minute, enabling faster ranger response

  • Reduced operational burden through AI-assisted monitoring and prioritization

  • Unified GIS dashboards providing live tracks, historical movement, and heatmaps

  • Increased operational resilience during connectivity loss and environmental stress

  • A scalable foundation for future capabilities such as event-driven patrols and sensor cross-cueing


Drone operations evolved from periodic observation into a persistent situational awareness capability.


MESH OS™ Operational Command Interface — a unified real-time view of assets, tracks, events, and wildlife activity, enabling rapid detection, context-aware decisions, and human-in-the-loop control across complex terrain.
MESH OS™ Operational Command Interface — a unified real-time view of assets, tracks, events, and wildlife activity, enabling rapid detection, context-aware decisions, and human-in-the-loop control across complex terrain.


Why This Partnership Matters


This project demonstrates the L19 AI Lab’s ability to deliver mission-ready AI systems, not experimental prototypes.


  • Designed for real environments, not lab conditions

  • Built with operator-in-the-loop governance by default

  • Deployed on-prem to meet sovereignty and security requirements

  • Integrated directly into defense-grade drone and GIS ecosystems


The same platform architecture is directly repeatable for national reserves, border and perimeter security, critical infrastructure protection, and public-safety surveillance missions.



For organizations interested in partnering with L19 AI Lab to deploy mission-ready AI capabilities, please contact our team at hello@l19.ai.


bottom of page