Datathon 2019

Posted shawarmataurusLeave a commentPosted in Datathons Solutions, Prediction systemsDatathons Solutions, Prediction systems

Datathon – Sofia Air 2.0 – Solution – (Virtual) forests to reduce PM10 pollution in Sofia

Sofia is a city with significant concentrations of particulate matter less than 10 micrometers in diameter (PM10.) A high concentration of PM10 is disruptive to life and the climate. The purpose of this project is to predict the concentration of PM10 at a particular day given the climatic conditions. This is important in allowing the making of policies to reduce the pollution in the city. Our contribution consists of a random forest regressor that acheives the purpose with 70 to 80% accuracy.

Posted 5yndr0m3, 5yndr0m3, pyro, marcel, iabdo3 CommentsPosted in Datathons SolutionsDatathons Solutions

Datathon – Sofia Air 2.0 – Solution – Predikt (Sofia Air 2.0) Github: scopyro

GitHub Accounts: KarimEid1, Marcel344, scopyro , @boudy87

Air pollution is quite a topic today. The municipality is investing a lot of effort and resources in order to measure the exact values of the gases and particulate matter in the air in order to identify its quality.

This is the next step towards the completion of a story and holistic view over the data-driven and explained the social topic of unveiling the secrets behind the information about Sofia Air Quality.

This research differentiates the main sources of pollution in Sofia and tries to predict what are the growing rate of this pollution in order to rise awareness against this danger and visualize, in numbers, its growth rate.