Sofia Air Case Advanced Approach

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Sofia Air Pollution Case Team BG-USA: Kristiyan Vachev – Bulgaria () Sergey Vichev – Bulgaria () Stefan Panev – Bulgaria Georgi Kirilov – Bulgaria Mike Lane – USA ()   Data Preparation Geocoding the construction data: The original source file can be found here.  Basically, this is very very similar to geocoding as proposed in the original documentation […]

(Virtual) forests to reduce PM10 pollution in Sofia

Posted Leave a commentPosted in Prediction systems

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.

Team Chameleons Air Solution

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Telelink Case Solution¶Team Chameleons¶ The Team¶vrategov kali stan caseyp Github Repo: 0. Data and working environment¶We were given the following 4 datasets: atmosphere_profile_train.csv – data from the University of Wyoming. It consists data for the temperature at certain height. construction_sites.csv – data for all construction sites in Sofia that are relevant for our time […]

Predikt (Sofia Air 2.0) Github: scopyro

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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.

Articles on Particles: Air Sofia Case by Wonder Gang

Posted 4 CommentsPosted in Datathons Solutions

Techonnology and methods used: R – tidyverse, lubridate, snakecase, sp, raster, spData, sf, leaflet, mapview, ggplot2, shiny, maps, devtools, geojsonio, rgdal, leaflet.esri, leaflet.extras Python – s3fs, pandas, numpy, matplotlib, plotly 1. Business Understanding Air pollution beyond the norms is a common problem in many locations. Examining the causes behind and being able to predict it would help control and reduce pollution, facilitate solving environmental issues and providing a better life to citizens. Air […]