Читать книгу Industrial Internet of Things (IIoT). Intelligent Analytics for Predictive Maintenance онлайн

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Within an IoT ecosystem, applications that integrate IoT technologies with Big Data technologies are operated, enabling the collection and analysis in real time of large data sets, allowing the development of predictive models for a variety of situations, from consumer behavior to the prevention of factory failures, and optimizing activities on the most varied fronts of activity. IoT technology brings changes both in the development of more pervasive connectivity and in the increase of data processing, derived from the refinement of sensors that allow data collection in different environments. All of this is associated with some practical solution allowing for increased efficiency, reduced human intervention, or even new business models [45], still evaluating that the AI generates a layer to enhance the value generated by the analysis of the different information captured and combined; allowing the automation of the decision-making process and actions in specific situations; bringing significant benefits to the increase in the speed of processes, reduction of the error rate due to human interference, and reduction of costs per transaction, in addition to the possibility of greater absorption of insights at each interaction that feedback and “teach” the AI algorithms (Machine Learning as an example); and making this incrementally more efficient [31].