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Prediction of air pollution with machine learning

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2019

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Gesellschaft für Informatik, Bonn

Zusammenfassung

Cities 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.

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Schmitz, Christian; Serai, Dhiren Devinder; Escobar Gava, Tatiane (2019): Prediction of air pollution with machine learning. BTW 2019 – Workshopband. DOI: 10.18420/btw2019-ws-34. Gesellschaft für Informatik, Bonn. PISSN: 1617-5468. ISBN: 978-3-88579-684-8. pp. 303-304. Data Science Challenge 2019. Rostock. 4.-8. März 2019

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