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Uni project combining the use of embedded systems and ML to predict the behaviour of temperature in a room

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agresdominik/seb_datascience

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SEB_Datasience: Room monitoring with Prometheus and Grafana

A brief description of what this project does and who it's for

Dependencies (On Debian based system)

These dependencies are needed to run the Project.
Run these commands (from root folder of project) to install the correct dependencies:

Docker (Newest version with compose plugin)

for pkg in docker.io docker-doc docker-compose podman-docker containerd runc; do sudo apt-get remove $pkg; done
sudo curl -fsSL https://download.docker.com/linux/debian/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
echo   "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/debian \
$(. /etc/os-release && echo "$VERSION_CODENAME") stable" |   sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Python (Tested and developed on 3.11.2)

sudo apt install python3 python3-pip

Python libraries

pip install -r ./src/requrements.txt

Environment Variables

To run this project, you will need to check and correct the following environment variables in the enviroment.py file

DHT_22_PIN

AIR_QUALITY_SENSOR_PIN

PHOTOSENSOR_PIN

PUSHGATEWAY_URL

Also create a api_key.key file with a openweathermap api key:

api_key=

Deployment

To deploy this project run

curl -O https://raw.githubusercontent.com/agresdominik/seb_datascience/refs/heads/main/services/setup/setup.sh | bash

Authors

Appendix

Any additional information goes here

Documentation

Confluence Internal

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Uni project combining the use of embedded systems and ML to predict the behaviour of temperature in a room

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