El-Vent
Medical IoT · Remote Ventilator Control
Medical-grade remote command & control for smart ventilators — real-time telemetry over MQTT/AWS IoT, ML respiratory analysis on SageMaker, AI anomaly detection for predictive maintenance.
The problem
Monitor and operate ventilators remotely with clinical-grade reliability: low-latency control, telemetry that never silently drops, and ML insight that supports — never replaces — clinical decisions.
System topology
Hover or tap any component. Amber packets carry control and approvals; cyan packets carry data.
Component inspector
Select any component in the topology to see the technology behind it, why it was chosen, and the trade-off accepted with it.
Decision log
The choices that shaped the system, and what each one cost.
The command path is sacred
Control messages travel the shortest possible path (console → API → IoT → device) with everything else — ETL, ML, dashboards — offloaded through RabbitMQ. Analysis can lag; commands cannot.
ML supports clinical decisions, never makes them
SageMaker models flag respiratory anomalies and predict maintenance; every output is advisory and surfaced with context. Mirrors the human-in-the-loop stance across all my AI systems.
Device identity as security foundation
Per-device mutual TLS through AWS IoT means a compromised credential is one revocation away from inert — not a fleet-wide incident.