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Aerial Object Detector

Enhance airspace awareness and safety in your UAS operations

The Problem

Low-level airspace is increasingly congested with drones, helicopters, ultralights, and other flying objects.

Many aerial vehicles do not emit collaborative signals (e.g., ADS-B, Remote ID), making them invisible to traditional tracking systems.

Non-cooperative objects (e.g., balloons, birds, hobby drones) pose real collision risks to both manned and unmanned aircraft.

Situational awareness tools often fail to detect these silent actors, especially below 400 feet, where most UAS operations occur.

The result: increased risk of mid-air conflicts, mission disruption, and safety concerns in critical operations.

The Solution

AOD

Aerial Object Detection (AOD) is a solution for real-time detection, classification, tracking, and geolocation of flying objects from IR and/or EO video streams, whether onboard drones or from ground-based sensors.

AOD brings state of the art AI to airspace monitoring

Get video


Get any type of video stream, in any format, from any sensor on board a drone or on PTZ cameras on the ground

Analyze


Automatically analyze video in real time

Detect


Detect, classify, track and geo-locate relevant aerial targets

Get alerts


Generate actionable alerts to enhance situational awareness and prevent collisions

Deploy Anywhere


Deploy on board, locally or on the cloud

AOD Benefits

Collision Risk Reduction
Enhance Situational Awareness and prevent mid-air conflicts by detecting flying objects not visible to traditional systems

Real-Time Intelligence:
Process live video streams to provide immediate alerts, supporting faster and safer decision making during missions

Non-Cooperative Object Detection:
Identify objects that do not broadcast their position

Flexible Deployment:
Deploy onboard, in the cloud, or at ground control stations

Operational Continuity:
Consistent performance in dynamic environments , supporting day and night, IR and RGB imagery

Efficient Resource Use:
Focus on relevant aerial activity, to optimize bandwidth, storage and operator attention

AOD Specs

Input Sources and Format:
IP Cameras; video files; video streams (RTP, RTSP, RTMP), video platforms (Milicast, Dolby.io, DJI).

Output Video Format:
Dolby, WebRTC,
RTMP, RTSP,
HLS

Integration:
REST API,
Sense Web Front
Mavlink

Alarms:
JSON over web socket,
Webhooks,
Serial for onboard deployments

Supported Camera Types:
IP cameras,
USB and GbE cameras for onbard

Supported Targets:
UAV,
Birds,
Gliders




Training Database:
+200.000 images

Latency:

<1 ms

Deployment:
Edge,
Cloud,
Private Cloud,
Local



Application Scenarios

For more information, Visit our youtube channel

Sense Aeronautics on Youtube

API Documentation

For more information about cloud integration, visit our API Documentation or send us an email