DroneWatch AI: Building a Multi-Sensor Drone Detection Demonstrator

Описание и применение

Демонстрационный проект DroneWatch AI объединяет пять слабых источников сигналов для обнаружения дронов, снижая ложные тревоги и предоставляя объяснимую оценку угрозы без дополнительного оборудования.

Задача

Commercial drones threaten critical infrastructure, but specialized counter‑drone hardware is expensive and coverage is sparse. Single sensors produce noisy false alarms that overwhelm operators.

Результат

The demonstrator shows that software fusion of existing sensors can reduce false alarms and provide clear threat assessments without additional hardware.

Рабочий процесс

• Collect live ADS‑B and Remote ID feeds
• Ingest radio‑frequency, acoustic, telemetry, registry, and human reports
• Apply deterministic rules to filter authorised flights
• Use AI layer to explain threat level
• Push scored track to existing command interfaces (ASTM F3411, ADS‑B, ASTERIX, U‑space/UTM, STANAG 4586/4609, Link 16)

Доказательства

The drone-threat signals are simulated. Two public feeds are live and real: ADS‑B air traffic and, since 25 September 2026, network Remote ID

Источник

A HIGH assessment requires at least two independent sensors to agree and a contact with no matching authorised flight

Источник

It stays strictly defensive: detection and early‑warning only, with any response left to a separate, authorised, human‑in‑the‑loop system

Источник