Why this decision matters
Embedded AI validation must cover model behavior, compute, memory, power, thermal limits, interfaces, dependencies, recovery, upgrade and field maintenance.
Retest on the target device or a close equivalent because a model running on a workstation does not prove stable operation on the deployed hardware.
Conditions to confirm before development
- Chip, accelerator, memory, storage and peripheral interfaces
- System image, driver, runtime, dependency and model versions
- End-to-end latency, throughput, power, temperature and endurance
- Power, network, sensor and input failures plus upgrade and rollback
Implementation and delivery approach
Version hardware, firmware, system, model and configuration together and test normal and abnormal conditions on the intended device path.
Deliver reproducible device tests, logs, firmware or image identifiers, deployment steps and maintenance notes.
Acceptance boundary
This guidance applies to the agreed data, system and environment. Project-specific scope, dependencies and acceptance conditions must be confirmed separately.