Yield prediction & Quality Model
A docker container to get the quality and yield predictions for the AI4AEU agriculture pilot
This component deploys a server that performs the yield and product quality predictions carried out in the AI4EU agriculture pilot. The component queries the different pilot data sources stored in a Knowledge Graph, provided also as a resource in the AI catalog, and generates a training set to generate prediction models to address the different queries sent as input.
The AI4agri quality and yield prediction model is a component that generates a set of different models depending on the data available in the pilot AI4Agriculture in order to predict yield and 3 different product quality indicators.
The component consists of a docker image (so having installed docker is a mandatory requirement), that can be complied from the source code available here.
To generate the docker image, it is only needed to use the command (in the same directory the dockerfile is located):
docker build -t <image-name> .
And then generate a docker container from that image:
docker run -d --name <container-name> -p <hostPort>:8061 <image-name>
It will expose the port defined as <hostPort> in order to serve the microservice defined here.