EAI EDGE RESEARCH CONCEPT

eAI Edge

Intelligent Edge Node with Neural-Interface Input

An in-development concept for a manifest-pinned eNI → eIPC → eAI research workflow. Hardware support, setup steps, and performance require validation on a named configuration.

v0.1.0

Current Version

v0.1

Profile

Config.

Hardware-Defined Channels

Pending

Power Validation

Planned Pipeline

The concept links three planned stages for acquisition, transport, and experimental inference.

eNI

Neural / Sensor Input

Research design for configuration-specific neural and sensor acquisition. Planned processing stages include filtering, spike sorting, and structured EIPC output.

eIPC

Secure Transport

Intended to route research data between eNI and eAI using configuration-specific integrity, encryption, and transport options.

eAI

On-Device Inference

Intended to evaluate manifest-pinned ML models on configured device accelerators or CPUs and publish research outputs through EIPC.

Illustrative Setup

Conceptual commands for a proposed workflow, not a verified deployment recipe.

# Clone the eAI Edge stack

$ git clone https://github.com/embeddedos-org/eAI

$ cmake -B build -DPLATFORM=rk3588s -DMANIFEST=manifest.yml

$ cmake --build build && ebuild flash

# Smoke test: verify all 3 pipeline stages are running

$ ebuild monitor --filter eai-edge

[simulated] eNI: configuration detected

[simulated] eIPC: transport check pending

[simulated] eAI: research model placeholder

Research Use Cases

Motor BCI Research

Concept pipeline for configuration-specific ECoG acquisition, experimental decoding, and assistive-control research.

Seizure-Pattern Research

Concept pipeline for EEG pattern-classification research. No detection performance, stimulation behavior, or treatment outcome is claimed.

Gesture Research

Concept pipeline for configuration-specific EMG acquisition and experimental gesture classification.

Cognitive-Indicator Research

Concept pipeline for studying EEG-derived fatigue indicators. No safety-critical monitoring performance is claimed.

EAI Platform Neural Link AI