Automatically Discover New MQTT Tags and Group By Asset

Some organizations constantly add new tags and assets to their operation.  If this is true for you, it is likely you or your team are spending too much time manually adding tags and assigning them to your asset model.  

Watch the video below to see how easy it could be!

Some organizations constantly add new tags and assets to their operation.  If this is true for you, it is likely you or your team are spending too much time manually adding tags and assigning them to your asset model.  

Watch the video below to see how easy it could be!

 

Cirrus Link really knows MQTT, in fact, the company's founder, Arlen Nipper, was the co-inventor of MQTT back in 1999.  In this collaborative project, Arlen and team have made two of their cloud hosted Chariot MQTT brokers available for the Canary MQTT Collector to subscribe to.  

 

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We begin with a very small sample of 600 tags and use these to build a Virtual View in the Canary System.  This Virtual View will create an asset model of the tags for our fictitious pipeline named 'CirrusLink Pipeline'.

Tags are grouped into the assets they represent, forming parent/child relationships.  Here is the top-down hierarchy:

  • Regions
  • Stations
  • Lines
  • Units
  • Tanks

We also built an Axiom application to allow us to visualize the assets.  This simple dashboard took about fifteen minutes and can show us an overview of our logging as well as a detailed page of each Unit and an overview of our Regions and Stations.

Screenshot (15)

Now, watch what happens when we begin logging all the remaining 135,000 tags!  Within 6 minutes the entire tag group is discovered, logged, and the Canary Virtual View automatically rebuilds.  Over 8,000 assets are then discovered and visualized on the Axiom application without any interaction from the client or a system administrator, it all just happens automatically!

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Learning more about Canary is simple.  DOWNLOAD OUR WHITEPAPER to learn how easy Canary can make it to get more value from your sensor data!

 

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