An AI-Driven Approach for Real-Time Noise Level Monitoring and Analysis

Abstract: Now a days, noise pollution is posing a public health risk, especially in residences and indoor environments like workplaces and schools. The proposed work presents a comprehensive analysis of hourly equivalent noise levels measured at 100 locations, such as the indoor environment. The proposed work is an intelligent automated noise pollution monitoring system for the real-time tracking and adaptive management of noise in indoor environments such as offices, homes, and educational institutions. Unlike other systems that merely record noise levels, the proposed solution provides real-time alerts with web-based visualization and AI-enabled noise pattern recognition for enhanced noise classification. The integration of an ESP8266 Wi-Fi module and a cloud-based architecture employs email notifications instantly, which also allows historical trend analysis and predictive insights. In addition, the framework is under-scope for the integration of smart home automation systems and mobile-based alerting, allowing for better accessibility. The IoT-powered innovations within this framework will revolutionize noise management by proactively monitoring, analyzing, and optimizing indoor sound environments. Through real-time adjustments and intelligent automation, these solutions will create a more serene, comfortable, and productivity-enhancing atmosphere. Whether in offices, homes, or public spaces, this advanced noise control system will contribute to overall well-being, concentration, and efficiency.

Yellamma Pachipala, L K SureshKumar, Veeranki Venkata Rama Maheswara Rao, Vijaya Chandra Jadala, T.Srinivasarao and D. Srinivasa Rao. “An AI-Driven Approach for Real-Time Noise Level Monitoring and Analysis”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.8 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160873

@article{Pachipala2025,
title = {An AI-Driven Approach for Real-Time Noise Level Monitoring and Analysis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160873},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160873},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {8},
author = {Yellamma Pachipala and L K SureshKumar and Veeranki Venkata Rama Maheswara Rao and Vijaya Chandra Jadala and T.Srinivasarao and D. Srinivasa Rao}
}