Skip to main navigation Skip to search Skip to main content

Recent trends in air quality prediction: An artificial intelligence perspective

    • Gazi University

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    9 Citations (Scopus)

    Abstract

    Many countries are suffering from air pollution due to imbalanced urbanization, unregulated increase in transportation, and inorganic industrialization. Air pollution directly affects the ecosystem and climate thereby compromising the well-being of the citizens and cities. For this reason, predicting air pollution in advance has a great importance in supporting proactive plans and environmental management actions for decision makers. In the literature, many research efforts are focusing on predicting air pollutant concentrations. In this chapter, we present recent artificial intelligence-based air pollution prediction approaches. In this context, we comprehensively reviewed the literature and categorized the proposed prediction methods based on feature selection methods, air pollutant types, and learning models.

    Original languageEnglish
    Title of host publicationIntelligent Environmental Data Monitoring for Pollution Management
    PublisherElsevier
    Pages195-221
    Number of pages27
    ISBN (Electronic)9780128196717
    DOIs
    Publication statusPublished - 1 Jan 2020

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities

    Keywords

    • Air pollution
    • Air quality
    • Artificial intelligence
    • Deep learning
    • Neural networks
    • Prediction methods

    Fingerprint

    Dive into the research topics of 'Recent trends in air quality prediction: An artificial intelligence perspective'. Together they form a unique fingerprint.

    Cite this