IoT and AI-Driven Noise Monitoring and Analysis System

This project develops an intelligent noise monitoring system using a high-precision wall-mounted noise sensor. The sensor measures sound levels in the range of -30dB to 120dB with exceptional accuracy and transmits data through an IoT platform for real-time monitoring, analysis, and remote access. Ideal for applications in urban noise management, industrial safety, and smart building systems, this project provides actionable insights for effective noise control.

AI algorithms process noise data to detect patterns, identify potential noise pollution sources, and predict trends. The system also generates alerts for threshold breaches, ensuring quick response to hazardous noise levels. A mobile app serves as a comprehensive interface for live noise level tracking, historical data visualization, and customized notifications.

Key Features:

• High-precision noise measurement with a range of -30dB to 120dB.
• IoT-enabled real-time monitoring and cloud data integration.
• AI-powered noise trend analysis and anomaly detection.
• Mobile app for live updates, alerts, and historical noise data visualization.

This project includes source code, complete hardware setup, detailed analysis, and a 200-page project report in soft copy, making it an excellent choice for students focusing on IoT and AI in environmental monitoring and urban management.