Architecture ‐ Iteration 2
Description:
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Data Service Integration Layer: Since we use face recognition on our IoT platform to make presonalized coffee possible, we integrated several (external) data services as AIAAS (AI as a service, to identify faces and learn about the preferences & behaviours of the different users) in combination with Big Data Analytics as a service (e.g. for maintenance and reporting of coffee maker usage data). Furthermore, we hosted our application on a cloud infracstructure (to ensure enough resources, high availbality and scalability). The manufacturer service platform is needed to guarantee a stable and smooth communication to the coffee maker.
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Process Engine Layer: The Process Engine Layer is responsible for the execution and optimization of a process set, which offers different processes based on credentials and circumstances. These credentials and circumstances are partly defined in the Business Rules Layer. Example: We have different users using our machine. The process differs from their preferences in case of coffee.
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Business Rule Layer: Different business cases need various business rules. The Business Rule layer contains rules for event- and exception handling, as well as various business cases & rules. For example: We have the case, that the coffe maker is too hot, which makes it dangerous to use it in this condition. We define a rule where we set the maximum operation temperature and if the machine exceeds it, the rule prescribes that the machine has to cool down before it can be used again.
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Device Management Layer: The Device Management Layer is used to connect IoT devices to IoT applications / platforms. In our case it connects the coffee maker to Rubi the Brewbot.