Live Aerial Target Tracking

Real-Time Aerial Object Detection & Tracking

HADES is an AI-powered tracking layer that carries moving aerial targets into the operator decision screen with low latency.

Explore decision line
HADES Live tracking line
Operator View JSON per detection, RTSP/HLS for video, H.264/H.265 recording
Confidence score Targeted mAP ≥ 0.8 after calibration (field-dependent)
30 FPS Processing speed

Up to 30 FPS (real-time video pipeline)

<100 ms Latency

Image → detection → metadata: typical < 100 ms (configuration dependent)

EO/IR Supported sensors

HD EO, IR/night mode, PTZ; adapters for radar, ADS-B, other telemetry

RBAC Security

TLS, JWT auth, RBAC, tamper-evident audit logs

Operational Signals

Target, track and event intelligence converge on one command surface.

HADES combines video streams, AI inference, multi-target tracking and secure metadata delivery into a single real-time decision line.

Target track Scales with compute/network — simultaneous N targets (configurable)

HADES is a real-time aerial object detection and tracking platform that uses AI-powered computer vision to detect and track moving aerial vehicles. Processing video at up to 30 FPS, HADES delivers high-confidence detections and actionable metadata to operator consoles via secure interfaces. Designed for situational awareness and both military and civilian applications, the system enforces human-in-the-loop decisioning, full audit trails, and strong security controls.

Decision Line

Readable target intelligence from camera to operator console

Instead of turning raw footage into static tables, the system shapes every step into a traceable mission flow.

01 Video Ingest

Streams from EO/IR/PTZ sources are processed in sync.

02 AI Detection

CNN-based models mark target candidates directly on the frame.

03 Multi Tracking

Target identities, motion trails and confidence scores stay updated.

04 Metadata

JSON, RTSP/HLS and event records flow into secure interfaces.

Capabilities

A real-time tracking experience that reduces operator noise

Real-time AI detection and multi-target tracking (up to 30 FPS)
Low-latency pipeline (typical < 100 ms) with secure APIs
Human-in-the-loop decisioning with full audit trail
EO/IR support, PTZ control, and radar/ADS-B integration
Scalable tracking capacity with modular deployment
Robust security (TLS, JWT, RBAC) and GDPR-aware processing
Technical Layer

Technical Specs

Processing speed Up to 30 FPS (real-time video pipeline)
Core algorithms CNN-based detection; Kalman/DeepSORT (or equivalent) multi-object tracking
Typical accuracy Targeted mAP ≥ 0.8 after calibration (field-dependent)
Output format JSON per detection, RTSP/HLS for video, H.264/H.265 recording
Tracking capacity Scales with compute/network — simultaneous N targets (configurable)
Environmental rating Typical hardware ranges: −20°C to +55°C (enclosure dependent)
Secure Operations

Project Info

Category AI, Computer Vision, Multi-Object Tracking
Scope Real-time aerial object detection, multi-target tracking, and secure metadata delivery
Communication protocols HTTPS/REST, MQTT, TCP/UDP; optional serial (RS-232/RS-422) with encryption
Storage & archiving Local/remote archiving, event DB, exportable logs
Compliance & privacy Configurable retention, GDPR-aware processing, audit trails
Architecture

Ingest → AI detection → multi-target tracking → metadata packaging → secure delivery to operator consoles. Enforces human-in-the-loop workflows, role-based access, and tamper-evident audit logs.

  • Modular video ingest with EO/IR and PTZ control
  • CNN inference and online tracker fusion
  • Secure APIs (REST/MQTT) and stream outputs (RTSP/HLS)
  • Event database, storage/archiving, and audit trails