Abstract
An algorithmic approach based on the methods of adaptive intelligent technology for monitoring the state of objects of computer systems is considered. The approach is focused on detecting changes in the state of controlled resources of autonomous information and measurement systems: communication channel, processor, memory, and battery. An adaptive model is presented using a Bayesian classifier for estimating changes in the state of resources of autonomous information and measurement systems. The model is based on a probabilistic automaton with adaptive self-tuning. The paper describes an approach that allows increasing the duration of continuous operation of the system for monitoring environmental parameters. This approach is based on adaptive correction of primary meter readings in the event of a decrease in their accuracy due to degradation failures.
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