This tool facilitates the incorporation of real data from a vehicle's sensors, stored in csv Datasets. Its purpose is to facilitate the development of algorithms responsible for processing the information that is collected and stored in this REDIS database within the Success6G project.
graph LR
Client(VEHICLE <br> INJECTOR) -- TCP/IP <br> (63790 / 127.0.0.1)--> Database(REDIS <br> DATABASE);
click Client "https://github.com/5uperpalo/success6g-edge/blob/main/tools/vehicle/vehicle_injector.py"
click Database "https://github.com/5uperpalo/success6g-edge/blob/main/configs/edge_redis.yaml"
Dataset[Dataset File] --> Client
classDef orange fill:#f96,stroke:#333,stroke-width:2px
class Dataset orange
Install the Redis database in your local development setup.
docker_compose -d configs/edge_redis.yaml
Verify docker container is running
docker ps -a
Run “Vehicle Injector“ script with dataset and station-id script:
python3 vehicle_injector.py -f <dataset_file.csv>