Let’s start with some IoT platform basics.
An IoT platform must cover four areas:
- Data storage
The platform connects machines, sensors and gateways to gather data about the status, the conditions and the usage over time. Divers protocol and interfaces have to be integrated.
The obtained data is stored in data bases. Depending on the later usage these data bases can either be structured or unstructured data bases with a fast data access for immediate reactions down to slow systems for sporadic use.
In order for humans to make decisions efficiently, a first overview of data in a simple dashboard is often enough. Correlations between data sets can be shown in a graphically way.
The data analytics can be supported by mathematics or even artificial intelligence. A lot of tools are available for this task. The business logic can add rules of decision, that can be executed by a machine.
Normally a logic is described by dependency graphs. They show the relevance of a situation, a condition of a machine or the order status in a ERP systems for the decision making process.
And by describing those in a machine understandable way it is possible, to automate decision sequences.
If customers ordered mineral water, I know I have it on stock, I can accept the order and deliver immediately.
If customers ordered mineral water, I know I don’t have it on stock, there are enough bottles to produce, I can accept the order and deliver after production.
With IoT we can add information directly from the productions line, the status of my warehouse, the prices of energy from the EEX (Leipzig energy exchange platform) and more in my decision process.
The latest technologies offer the business decider the necessary tools, to describe these processes in a graphical way. No coding needed. This avoids communication failures between business and IT and speeds up the process of changing structures. Here is an example created in NodeRed, an environment to describe logical dependencies.
However, it is important to note that systems like NodeRed show some disadvantages. Like security issues that are created by running customer code or the issue of scalability.
I/O.nite solves these problems and offers a solution based on a rules engine to describe logic and to execute decisions in a save and performant way.
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