Artificial Intelligence (AI) and its Applications in Engineering

The intervention addresses the role of artificial intelligence in improving air pollution predictions in urban neighborhoods. The theoretical framework of artificial intelligence techniques and their potential applications in enhancing air quality predictions at the neighborhood level is analyzed. Research on the application of machine learning methods to improve air pollution predictions in urban neighborhoods is reviewed. The focus is on the analysis of the theoretical models used in air emission predictions and the evaluation of models used in air quality predictions at the urban neighborhood level. Anticipated outcomes from the application of artificial intelligence without practical implementation are identified, along with an analysis of previous relevant studies on air pollution predictions in urban neighborhoods. The conclusion emphasizes the importance of the theoretical study in improving air pollution forecasts in urban neighborhoods

• Air pollution prediction
• Machine learning
• Enhanced prediction
• Artificial intelligence integration
• Theoretical models
• Air emission forecasts
• Time series analysis

• Air pollution prediction
• machine learning
• Enhanced prediction
• Artificial intelligence integration
• Theoretical models
• Air emission forecasts
• Time series analysis