The application discloses a kind of multi-sensor AI model training and embedded deployment method and
system, the
system includes: request monitoring module, parameter
verification module, task scheduling module, execution engine module, model training module,
storage management module, model deployment module;The method comprises: back-end service receives the model training request initiated by
client, and verifies the legality and parameter integrity of the request;In
distributed cache, whether the lock mark corresponding to unique
fingerprint exists is inquired;The task context of this time is distributed to independent sub-process or work thread, according to the preset sensor type-model training strategy mapping table, different types of sensor data are routed to the corresponding model training strategy;After model training is completed, model file and evaluation report are output to storage backend, and back-end service receives the model deployment request initiated by
client, and
client issues model file and deployment
metadata to deployment equipment, to provide intelligent support for model construction.