The right kind of data to use for industrial IoT (IIoT) within your IoT platform (and beyond) depends on your specific use case and your individual requirements, however there are some common types of data that are commonly used in IIoT:
Advanced industrial IoT platforms, (such as Rayven's platform), are capable of handling data from multiple sources in real-time; key to this is their interoperability and integrations, as well as the ability to easily configure and display in simple, always accessible, dashboards and reports.
The right kind of data to use in IIoT will depend on the specific use case and requirements of the organisation. For example, if an organisation is looking to improve production efficiency, then machine data and process data would be the most relevant. If an organisation is looking to improve maintenance operations, then maintenance data coupled with real-time asset performance data would be the most relevant.
It is therefore important to consider the data that is most relevant to the specific use case and requirements of the organisation, and ensure that the data is accurate, complete and relevant to the specific use case. Rayven provides prebuilt IoT solutions that comes largely preconfigured (leaving room for you to customise and tailor the parts that matter), meaning that you have a blueprint for the data that you need to collect and much of the hard work in terms of workflows and processing is already set-up for you, including machine learning algorithms.
In summary, the right kind of data to use in industrial IoT depends on the specific use case and requirements of the organisation. Common types of data used in IIoT include machine data, process data, maintenance data, environmental data, business data, and sensor data. It's important to consider the data that is most relevant to the specific use case and requirements of the organisation and ensure that the data is accurate, complete and relevant to the specific use case.
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