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Sentinel Core
The foundational framework for autonomous video intelligence and surveillance.
Pitch

Sentinel Core serves as the essential open-source framework for high-performance surveillance and situational awareness. With robust support for multi-protocol stream handling and modular architecture, it ensures reliable, low-latency processing across various platforms, making it ideal for mission-critical environments.

Description

Sentinel Core is the foundational open-source framework of the Sentinel platform, expertly designed for mission-critical surveillance and autonomous video intelligence. It equips developers with essential architectural components for high-performance operations, including object detection and multi-stream camera management. Key attributes of Sentinel Core include:

  • Mission-Critical Capabilities: Tailored for environments that demand reliability and low-latency processing.
  • Modular Pipeline Architecture:
    The framework features a structured pipeline that includes:
    • Ingestion: Capable of multi-protocol stream handling (RTSP, RTMP, Local).
    • Detection: Offers abstraction layers for AI model inference using well-known models like YOLO and CLIP.
    • Intelligence and Spatial Awareness: Implements data schemas for persistent tracking and alert mechanisms that detect zones, intrusions, and loitering analysis.
    • Sovereign Alerting: Utilizes standardized protocols to deliver alerts securely through various channels, including Telegram and Webhooks.
    • Evidence Persistence: Enables high-fidelity video recording, integrating pre-event buffering and automated segment management for effective data retention.
    • Hardware Acceleration: Optimized for NVIDIA CUDA and Apple Silicon, ensuring performance enhancement on institutional-grade hardware.
    • Tactical Dashboard: An intuitive web interface for real-time monitoring and natural language querying of forensic data.

Performance Metrics:
Sentinel Core is built to handle high-frequency video processing with benchmarks demonstrating robust throughput metrics:

LayerHardware SubstrateResolutionThroughput
Detection (YOLO)Apple M2 Max1080p~85 FPS
Detection (YOLO)NVIDIA RTX 40901080p~140 FPS
Semantic SearchApple M2 Max1080p~12 FPS
Semantic SearchNVIDIA RTX 40901080p~25 FPS

Before deploying in a specific environment, performance can be individually verified with a benchmarking utility. Code snippets provided in the README illustrate how to implement a custom situational awareness detector and initiate a stream session smoothly.

Evolution of Sentinel Core:
The framework is continuously evolving, with regular updates reflecting the advancement of features and improvements in functionality, as outlined in the version history.

Understanding Surveillance Through Innovation

Surveillance transcends mere video capture; it is about achieving autonomous situational awareness. Sentinel Core facilitates the transition from raw data to strategic operational intelligence, enabling users to harness video data in meaningful and impactful ways.

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