Implementing machine learning in local APL edge devices with power limitation

A method performed by an Advanced Physical Layer (APL)-based edge device with power limitation is provided. The method includes applying an event-driven framework that conforms to a power limit of an APL-based edge device to receive input data; an event-driven framework is applied to the input data to invoke a machine learning (ML) model trained to analyze the input data and make inferences about one or more aspects of the industrial system based on the input data, and applying the invoked machine learning model to analyze the input data and make inferences about one or more aspects of the industrial system based on the input data. The APL-based edge device receives input data from one or more source field devices of the industrial system and/or uses inferences to make decisions and apply actions to the industrial system. 提供了一种由具有功率限制的基于高级物理层(APL)的边缘设备执行的方法。该方法包括应用符合基于APL的边缘设备的功率限制的事件驱动框架来接收输入数据；将事件驱动框架应用于输入数据以调用机器学习(ML)模型，其被训练以分析输入数据并基于输入数据做出关于工业系统的一个或多个方面的推断，以及应用被调用的机器学习模型来分析输入数据并基于输入数据做出关于工业系统的一个或多个方面的推断。基