IoT and AI medical capsule

Three stacked layers. A physical edge of rugged sensors and edge processors; an intelligence core running real-time AI and an RTOS; and a digital cloud for analytics and model training. Data rises from the edge to the cloud, and trained models return to the edge, closing the loop.

1. Layer 1 of 3: Physical edge. Rugged sensors and edge processors that survive heat, dust and vibration.
   • Sensor array — Environment heat, dust, vibration
   • Power stage
   • Edge processor — Role acquisition and control
   • I/O
   • Actuator
2. Layer 2 of 3: Intelligence core. A real-time AI + RTOS layer making zero-latency decisions at the edge.
   • RTOS — Scheduling deterministic
   • Inference — Decision point at the edge
   • Control loop
3. Layer 3 of 3: Digital cloud. Scalable analytics and model training that feed evolved models back to the edge.
   • Analytics
   • Model training — Output evolved models to the edge
   • Fleet management

Connections:

• Sensor array delivers measurements to Edge processor.
• Edge processor issues actuation commands to I/O.
• Power stage delivers drive current to Actuator.
• Edge processor passes data up to RTOS.
• RTOS schedules Inference.
• Inference supplies setpoints to Control loop.
• Inference passes data up to Analytics.
• Analytics supplies datasets to Model training.
• Control loop passes data up to Fleet management.
• Model training returns trained models to Inference.
• Fleet management returns updated operating policy to Control loop.