Physical AI Infrastructure

Physical AI Infrastructure
Hardware, software and networks supporting embodied intelligent systems
Category	System architecture
Area	Artificial intelligence, robotics and connected systems
Related concepts	Edge AI, Sensor Fusion, Robot Identity Management

Physical AI infrastructure consists of the computing, sensing, control, networking and operational systems used to develop or run AI-enabled physical machines. The exact architecture depends on whether the system operates in a factory, road environment, laboratory or other setting.

Physical layer

Sensors, actuators, motors, batteries, power electronics and controllers connect computational decisions with real processes. Hardware choices constrain motion, power use, sensing quality and safety.

Compute and services

A system may combine embedded computing, edge inference, external services, simulations, data storage and fleet-management tools. Local processing can reduce dependence on remote communications for selected functions.

Operational lifecycle

Infrastructure includes secure updates, inventory, key management, monitoring, calibration and maintenance. Engineering should consider whether the machine can enter a safe state during loss of network access or other faults.

See also

• Edge AI
• Sensor Fusion
• Robot Identity Management