Challenges of real-time AI/ML computations

We will start from the examples that we faced as Data Science practice at InterSystems:

  • A “high-load” customer portal is integrated with an online recommendation system. The plan is to reconfigure promo campaigns at the level of the entire retail network (we will assume that instead of a “flat” promo campaign master there will be used a “segment-tactic” matrix). What will happen to the recommender mechanisms? What will happen to data feeds and updates into the recommender mechanisms (the volume of input data having increased 25000 times)? What will happen to recommendation rule generation setup (the need to reduce 1000 times the recommendation rule filtering threshold due to a thousandfold increase of the volume and “assortment” of the rules generated)?
  • An equipment health monitoring system uses “manual” data sample feeds. Now it is connected to a SCADA system that transmits thousands of process parameter readings each second. What will happen to the monitoring system (will it be able to handle equipment health monitoring on a second-by-second basis)? What will happen once the input data receives a new bloc of several hundreds of columns with data sensor readings recently implemented in the SCADA system (will it be necessary, and for how long, to shut down the monitoring system to integrate the new sensor data in the analysis)?
  • A complex of AI/ML mechanisms (recommendation, monitoring, forecasting) depend on each other’s results. How many man-hours will it take every month to adapt those AI/ML mechanisms’ functioning to changes in the input data? What is the overall “delay” in supporting business decision making by the AI/ML mechanisms (the refresh frequency of supporting information against the feed frequency of new input data)?

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I would like to know any experience working with OPC UA standard in industry sector or IoT. Currently there is no adaptor implemented in IS IRIS for it but it seems to be pushed as the main standard in industry. Did anyone had to implement their own libraries or adaptors to deal with it? Or do you advice to use any already implemented library in Java, Python,...? Any feedback would be appreciated. 

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Presenter: Michael Broesdorf
Task: Use the Internet of Things in a business application
Approach: Demonstrate incorporating device-generated messages into a business process, and using that information to trigger physical events

(Session Sequence: Dependent on EOPEN) IoT may be the most hyped idea of the year, but how do you actually make use of it in your business applications? This session gives a detailed demonstration of incorporating device generated messages into an business process, to interact with your business applications and triggering physical events as a part of a business process.

Content related to this session, including slides, video and additional learning content can be found here.

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This is a nice introductory explanation of MQTT that I thought would be of general interest. The technology used for the broker in this case is not that important as there are several brokers available.

At global summit we will be demonstrating ways to use MQTT with Ensemble to get information from the Internet of Things into your enterprise applications and business processes,


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