A sensor reads potentially critical data from an industrial device, but most of the data from the sensor is not critical information and does not change unless a critical event happens.
Which data work flow is appropriate for how the critical and non-critical data is processed?
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A. B. C. D.D.
The appropriate workflow for processing critical and non-critical data from a sensor in an industrial device depends on the specific requirements of the application. However, given the information provided in the question, option A seems to be the most appropriate workflow. Here is a more detailed explanation of each step in this workflow:
Acquire sensor data: The first step is to acquire data from the sensor. This can be done using various methods, such as wired or wireless communication protocols. The data is then sent to an edge device or gateway for processing.
Filter non-actionable data: Since most of the data from the sensor is not critical, it needs to be filtered out to reduce the amount of data that needs to be processed. Filtering can be done at the edge or gateway device, using rules-based or machine learning-based algorithms. The filtered data is then sent for further processing.
Perform action on data: The filtered data is processed to determine if any critical event has occurred. If a critical event has occurred, appropriate actions need to be taken, such as shutting down the device, sending an alert to an operator, or taking any other necessary action to prevent damage or loss. The action can be performed at the edge device or gateway itself or by sending instructions to the industrial device.
Send critical data and action performed on data to cloud for storing: Once the critical data has been identified and the necessary action has been taken, the critical data along with the information about the action performed on data is sent to the cloud for storing. The cloud can be used for further analysis of the data, long-term storage, and to provide insights to stakeholders.
This workflow ensures that only critical data is processed, reducing the load on the system and preventing unnecessary actions from being taken. It also provides a mechanism for storing critical data for future reference, analysis, and reporting.