Schmitz, ChristianSerai, Dhiren DevinderEscobar Gava, TatianeMeyer, HolgerRitter, NorbertThor, AndreasNicklas, DanielaHeuer, AndreasKlettke, Meike2019-04-152019-04-152019978-3-88579-684-8https://dl.gi.de/handle/20.500.12116/21822Cities worldwide are facing air quality issues, leading to bans of vehicles and lower quality of life for inhabitants. We forecast the air quality for Stuttgart based on expected weather condition. For that purpose, we extract, cleanse, and integrate the DHT22 and SDS11 sensors’ data to feed two different machine learning models for predicting the particulate matter values for the near future.enData Science ChallengeBig Data Analytics10.18420/btw2019-ws-341617-5468