coffee machine 4.0 & expert on demand (IoT/M2M/Industry 4.0/Wearable Glass Technologies)
looking for use cases of wearables, m2m or iot?
the following presentation was shown on teched:
the device: a connected coffeemachine with SIM card
All data of the coffeemachine is pushed to a cloud (in our case IOT Platform with Hana Database), and we are able to create realtime-dashboards including predictive values which are calculated by hana on-the-fly.
in case of an alert, a service request is generated in the sap erp backend system, dispatched and pushed to the Tablet of a service technician (including all Data on location, involved devices/equipments, spare parts etc)
once the technician arrives on-site, he can use a wearable/glass so he has his hands free to fix the machine. On the Glass, 2 apps are installed:
a) 3D-Video Animation of the Instruction/Reparation Manuals created with SAP Visual Enterprise (from the manufactors CAD Graphics)
b) Video Conferencing Solution Vidia: call of an ‘Export on Demand’ who seats in a remote location and sees through the wearables camera what happens on-site, he’s able to communicate, show additional documents and give valuable tipps
at the end, a missing spare part is printed from the CAD Model on a 3D Printer
Overview of the Scenario:
see all items life in action as shown in teched berlin 2014:
http://events.sap.com/teched/en/mobile/session/13830
whats next??
i am thinking of combining the data with weather history & forecast data, predictive maintenance scenarios or a small robot bringing me coffee
what do you think?
IoT is definitely one of the major topics to come within the next years. This blog gives an excellent insight in what we can expect and what the possibilities are. Swisscom has combined the major components into one really sound scenario: sensors delivering constant data streams into a big data environment, an analytics layer using predictive scenarios, usage of next-generation tools (like wearables/glasses and 3D printers) including full integration into an every-day business process (in this case service maintenance for a coffee machine). I think we should integrate real time traffic data into the predictive analysis scenarios thus calculating the fastest way for the service technician to my broken coffee machine 🙂