FIELD: physics.
SUBSTANCE: invention relates to a method of detecting training data for machine learning of a computer system of the industrial Internet of things powered by rechargeable battery. Method comprises interaction between an industrial Internet of things (IIoT) system, a training data detection system and a training data processing and storage system, during which contextualized training data are detected in remote databases in computer systems for processing and storing training data with access via an Internet communication network by analysing the correspondence of the semantic annotation of the training data and the semantic description of objects and parameters of the industrial Internet of things in the form of concepts and attributes of the industrial Internet of things ontology concepts, as a result of which a command signal is generated to increase the charge consumption of the rechargeable battery for the device using machine learning to start the machine learning program in an Internet of things computer system powered by a rechargeable battery.
EFFECT: longer autonomous operation of an industrial Internet of things computer system powered by a current charge of a rechargeable battery using machine learning.
2 cl, 2 dwg, 2 tbl
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