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