At the recent GE Edge Symposium at its Global Research Center campus outside Albany, New York, the company outlined some of the initiatives and real-world applications that are leveraging the recently announced Predix Edge System, which is the new rollout of the year-old Predix IoT analytics system.
The first example was in the so-called Internet of Elevators world. In this case study, a modem controller has been placed in Schindler elevators and the company is scaling to 300,000 devices this year, and 1 million next year. This is one of the field programs in which GE is paving a path to predictive analytics. The path begins by collecting data about events at the edge, which in this example, means floor arrivals and opening of the elevator doors, usually. GE is using an event processor by partner Foghorn to collect that event data and feed it to the Predix analytics engine.
Up next on the path to predictive is the analytics, which takes place within the Predix platform, and centers on algorithm development, progression and improvement of the production flow, always improving in incremental steps as the data store becomes ever deeper.
This whole flow has now been combined into the Predix Edge, which will link the intelligence from devices at the edge, the device manager and the asset performance management software.
In the IoT Healthcare space, GE Health is a clear leader, and the Edge Symposium gave us some peeks at the IoT enabled health tech they’re putting out there to improve patient outcomes. The GE Healthcare BioReactor is a machine that makes drugs which must be grown at the cellular lever under very specific conditions. In the case presented, the lab makes cancer drugs that are targeted to a specific patient and that patient’s cancer’s physiology, and it’s used as a last resort for very late stage patients.
While the medicine is being prepared over the course of two weeks, any disruption can ruin the whole batch, and so the GE Health solution allows the manufacturing company to attach GE’s mini-field agent edge processing device up to the preparation unit, where it collects data on the status of the mechanism, monitors that status, uploads data periodically to the Predix cloud and uses that data and analytics at the edge to determine if the conditions are right to start the two-week process. This is critical because if the process doesn’t work, the patient who needs it will often not live to see the new batch completed.
So that’s a pretty important system.