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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Pollution and Weather Reports: Using Machine Learning for Combating Pollution in Big Cities.

Cicerone Laurentiu Popa1, Tiberiu Gabriel Dobrescu1, Catalin-Ionut Silvestru1

  • 1Robots and Production System Department, University Politehnica of Bucharest, Splaiul Independenței 313, 060041 Bucharest, Romania.

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Summary

This study uses machine learning to predict air quality index behaviors and temperature evolution based on pollution levels. The research validates a model using data from Bucharest, Romania, highlighting prediction errors.

Keywords:
machine learningpollutionsensorssmart city

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Area of Science:

  • Environmental Science
  • Computer Science
  • Data Science

Background:

  • Air pollution poses a significant threat to human evolution and planetary ecosystems.
  • Technological advancements, including the Internet of Things (IoT), are enabling new approaches to monitor and control air pollution.
  • Accessible monitoring devices have spurred innovation in environmental management.

Purpose of the Study:

  • To predict air quality index (AQI) behaviors using machine learning algorithms.
  • To analyze the relationship between temperature and pollution levels.
  • To develop and validate a predictive model for air quality in Bucharest, Romania.

Main Methods:

  • Collected air quality data from atmospheric stations in Bucharest.
  • Employed three distinct machine learning algorithms for analysis.
  • Studied the evolution of temperature in relation to pollution factors.
  • Validated the model's performance using Root Mean Square Error (RMSE).

Main Results:

  • Presented results of machine learning algorithms for predicting air quality.
  • Analyzed pollutant types and their impact over two distinct periods.
  • Quantified prediction errors using RMSE for each algorithm.
  • Demonstrated the model's ability to forecast air quality trends.

Conclusions:

  • Machine learning models can effectively predict air quality index behaviors.
  • Understanding temperature-pollution dynamics is crucial for environmental management.
  • The validated model provides insights into air quality evolution in urban areas.