Urban Noise Classification Using Machine Learning Algorithms
This study presents a comprehensive approach to urban noise classification using various machine learning algorithms. The research focuses on developing efficient classification systems for different types of urban environmental sounds, contributing to smart city applications and noise pollution monitoring. The proposed methodology demonstrates effective performance across multiple noise categories in urban environments.
Urban Noise Classification Using Machine Learning Algorithms
This study presents a comprehensive approach to urban noise classification using various machine learning algorithms. The research focuses on developing efficient classification systems for different types of urban environmental sounds, contributing to smart city applications and noise pollution monitoring. The proposed methodology demonstrates effective performance across multiple noise categories in urban environments.
Key Highlights
- Comprehensive approach to urban noise classification using various ML algorithms
- Efficient classification systems for different types of urban environmental sounds
- Contributing to smart city applications and noise pollution monitoring
- Effective performance across multiple noise categories in urban environments
Technologies Used
- Urban Noise Classification - Environmental sound categorization
- Machine Learning - Algorithm-based pattern recognition
- Environmental Sound Recognition - Audio analysis and identification
- Smart Cities - Urban technology applications
- Noise Pollution - Environmental monitoring systems
- Audio Signal Processing - Sound data analysis techniques
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