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Operating System for Controlled Environment Agriculture
Depends on #5
This aims to create objects that latch onto sensors, and produce analyses of the information read by the sensor. Requires changing the sensor interface, and creating a new Analytic object type. These objects will have an analyze method that requires implementation.
Write actuator interface for WeMo smart plugs.
Create a YAML file that defines environmental parameters depending on growth stage.
Implement different types of autogrowers which have different control algorithms.
Let's configure grafana with bind mounts or some solution that allows people who clone and run this repo to see a quality dashboard from the jump!
Depends on #4
Writing test cases for all objects
In order to facilitate communication between Grafana or other automated actors and CEA-OS, it would be beneficial to have a REST API to deal with commands given to actuators in CEA-OS, or even data input into CEA-OS
I'll work on encoding images captured by our cameras to base64 (plaintext string format). We can send this text string to InfluxDB through our logger interface.
My plan is to create a module with an image class (unless there's an existing script I should directly add this to). The class would have a member variable for the filename of the image, as well as member functions to encode and decode the image data.
Is this on the right path? Then I think the next issue would be to display these images on Grafana.
Create a workflow for image processing
Depends on #3
Splitting from #7
The artificial sensor should implement the sensor definition here: /cea-os/sensors/sensor_definition.py. It should allow the user to set the output value of the sensor, and add some random noise.
Need to create skeleton objects for environments.
Proposed skeleton:
Object:
sensors:{list of tuples ('name',Sensor Object)}
Set up containerized build of system that builds a docker container for this repo.
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