Counter UAS
Drone detection and tracking
Neuromorphic Vision Intelligence
EtherX builds complete event-based vision systems, from AI algorithms to edge hardware, for real-time detection, tracking, and motion analysis of satellites, debris, drones, and aerial entities.

EtherX.AI
The next generation of intelligent machines will view the world differently! They will respond only to the dynamics of the world.
At EtherX.AI, we are building next generation intelligent perception systems using neuromorphic/event cameras that capture visual change asynchronously at extremely fine temporal resolution. We are putting this technology to work on one of the most demanding perception challenges today, namely, real-time detection and tracking of small, fast-moving drones.
Conventional cameras capture complete images at fixed intervals, even when most of the scene remains unchanged. A neuromorphic event camera works very differently. Each pixel responds independently when it detects a change in the corresponding intensity, producing a sparse and asynchronous stream of visual events.
For small aerial targets, this is a powerful advantage. A drone may occupy only a few pixels on an image sensor, accelerate rapidly, change direction abruptly, or move significantly between consecutive video frames. A neuromorphic event camera does not need to wait for the next frame. It captures change dynamically as it happens.
At EtherX.AI, we have developed a complete neuromorphic processing pipeline that transforms asynchronous neuromorphic data into real-time drone detection and continuously updated target trajectories. The complete perception pipeline operates at millisecond-scale latency, enabling rapid response to fast target motion. Our system maintains robust, uninterrupted tracking under challenging conditions, including sun-glare, rain, multiple drones, and noisy environments
Event Sensor
Neuromorphic
Processing Pipeline
Localization and Tracking
The pipeline is being optimized, quantized and deployed directly on edge hardware, reducing latency, bandwidth and dependence on cloud computing. Our goal is to build intelligent systems that are compact, power-efficient and ready for real-world deployment. This enables a new generation of intelligent systems across high-speed and edge-sensing applications.
Drone detection and tracking
Airborne collision awareness
Perimeter and asset monitoring
Fast motion perception
Efficient edge monitoring
Responsive trajectory estimation
As seen in these demo videos, the conventional RGB camera struggles to maintain reliable drone detection and tracking under challenging illumination due to its limited dynamic range and frame-based acquisition. In contrast, the neuromorphic camera provides high dynamic range and microsecond-scale temporal resolution, enabling more robust and continuous tracking under strong contrast, shadows, and rapid motion.
Hardware Platform
HOMI is our end-to-end EdgeAI platform, combining a high-speed event sensor with FPGA compute and our in-house AI accelerator in a compact board designed for deployment in space, aerial, and defense systems.
10x5cm
Compact form factor
Sub-ms
Ultra-low latency architecture
On-device
Full edge inference - no cloud
Multi-task
Detection, tracking & classification - simultaneously
Front view

Top view

Asynchronous, sparse event-driven output that captures only change in the scene with microsecond temporal resolution.
FPGA-based compute backbone with hardware-optimized preprocessing pipelines and headroom for multi-task deployments.
Quantization-aware neural network accelerator optimized for sparse event data across detection, classification, and tracking.
10 cm x 5 cm form factor designed for edge deployment in satellites, UAVs, ground stations, and embedded systems.
01
Compute velocity vectors in real time from sparse event streams for trajectory prediction at speeds frame cameras cannot resolve.
02
Continuously detect and track satellites, debris, drones, and aerial objects using event-based clustering and centroid trajectories.
03
Distinguish satellites from stars and clutter in dense fields using AI models trained on event-based motion signatures.
04
Run real-time trajectory analysis and motion prediction to estimate collision risk and enable early warning.
No motion blur and no missed fast events.
Only changing pixels generate data.
Handles dark space and sunlit objects without saturation.
Full inference near 1 ms latency with ultra-low power.
HOMI and our algorithm stack are domain-agnostic. If it moves fast and you need to understand it in real time, we can track it.
Track satellites and orbital debris in LEO, detect tumbling behavior, support collision avoidance research, and analyze object attitude.
Detect and track UAVs, drones, and low-altitude flying objects in real time even in cluttered visual environments.
Enable autonomous airspace surveillance with ultra-low-latency threat detection and on-device inference.
Use a full-stack neuromorphic testbed from event preprocessing to on-device AI with flexible latency/accuracy studies.
Whether you are working in space operations, defense, aerial robotics, or research, we bring neuromorphic hardware and AI algorithms to turn raw events into real-time intelligence.
Contact us