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Step #NameDescriptionOutputImplementation Flow
1Gather Metadata

Input to gathering of metadata step can be:

  • Manual entires
  • Code that generates metadata
  • Reading metadata from external device management source

The output of gathering metadata step could be:

  • Generated CSV, JSON Files
  • Generated Create / Save TQL Query statement
  • Emulate automatic trigger for sensors@TQL Macro, AppModel, AppFacet
  • Gather and Initialize can be combined into same flow.
  • Decoupled implementation from TQLEngine
    (Example: NodeJS generating series of JSON files)
2Initialize

Initialize step is where we load includes:

  • Load the data into TQLEngine.
  • Metadata gathered from step-1 serves as input
to initialize
  • .
  • This steps has to be repeatable.
  • Simple Sensors and Actuators
  • JavaScript to capture simulation logic
  • Schedule frequency of simulation

Bulk Initialization Steps: 

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Simulating Temperature Sensor

Simulation Logic

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GHTempAdj On Sunnyday: formula to calculate GHTempAdj in Celcius: GHTempAdj = (100/(CurrentTemp+237.1))3 * 100

For example, when (external) CurrenTemp = -5 Celcius, GHTempAdj = 5.186; when CurrentTemp = 28 Celcius, GHTempAdj = 3.661

On NOT Sunnyday: formula to calculate GHTempAdj in Celcius: GHTempAdj = (100/(CurrentTemp+237.1))3 * 60

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The output of initialize steps are:

  • Data and Things loaded into TQLEngine.
  • May or may not note trigger actions.
  • @TQL Query
  • Can be integrated into Gather Metadata step.

Bulk Initialization Steps: 

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Greenhouse UseCase

Please refer to 8. Simulating sensors, actuators, and devices for the description of Greenhouse usecase. The data initalization requirement for this case is shown below

Greenhouse Configurator Application Flow

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Requirements

  • Ability to add greenhouses on-the-fly
  • Each greenhouse must be able to dynamically generate number of lanes, zones per lane
  • Add Crop type per lane

Add Greenhouse and Heater Model

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