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@article{164316,
        author = {Prathmesh Vhasale and Mayur Waghmare and Piyush Wardhe and Medha Wyawahare},
        title = {Comprehensive Noise Analysis: Monitoring and Comparative Classification Models},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {1367-1375},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164316},
        abstract = {This project combines hardware and software components to monitor sound levels in various environments, particularly focusing on noise-restricted zones. The hardware setup involves a sound sensor module and an Arduino microcontroller to calculate and display sound decibel levels continuously. The software aspect employs machine learning techniques to classify audio samples based on their sound characteristics. Specifically, the UrbanSound8K dataset is utilized for training and testing classification models. Various algorithms such as Support Vector Machines (SVM), Random Forest, and Decision Trees are implemented and evaluated for their accuracy in classifying sound samples.},
        keywords = {UrbanSound8K dataset, Support Vector Machines (SVM), Random Forest, Decision Trees, Audio classification, Machine learning},
        month = {},
        }