Project for team Kyychi in Junction 2018.
- Use cases: https://drive.google.com/file/d/1xRJzWirQYlfuo3qtC0h2v4aHMFd6eD4Y/view
- Google drive: https://drive.google.com/drive/folders/19ptwz2_PHNWmPEFSqyjegbi3GwHMgaH2
- Junction challenge page: https://2018.hackjunction.com/challenges/wisdom-of-crowds
- Install Docker, Docker-compose and Yarn.
- Run
docker-compose up -d
to start PostGIS database. - Run
yarn install
to install required packages.
Shuffle files around:
mkdir data
cp teliaData/Footfall\ data/Shapefiles/Uusimaa_ff_grids.* data
cp teliaData/Footfall\ data/*.txt data
cp teliaData/Activity\ data/Shapefiles/FI_MTC_WGS84_update.* data
cp teliaData/Activity\ data/*.txt data
Imports data into the postgres database.
- Start the compose stuff.
- Run it once by running
yarn run import:crowd
. - Run
docker-compose restart
.
Simple webpage that renders the predictions as a heatmap.
Run it by running yarn frontend
. Browse http://localhost:3000.
Machine learning project that predicts how many people there will be based on different parameters.
cd weather
- Run
python3 -m venv venv
- Run
source venv/bin/activate
- Run
pip install -r requirements.txt
- Run
./start.sh