Description:

The Noise Pollution Mapping Tool is a web-based environmental monitoring system that collects real-time sound level data from IoT-enabled noise sensors installed in various locations. It visualizes noise intensity on an interactive city map, helping citizens, urban planners, and government agencies identify high-noise zones and take preventive actions.

By storing historical sound data and applying trend analysis, the platform can predict future noise patterns during events like festivals, construction work, or peak traffic hours.

Key Features:

1. Real-Time Noise Level Monitoring – Collects decibel (dB) readings from IoT sound sensors.

2. Interactive Map Visualization – Displays noise intensity using color-coded heatmaps (green for safe, red for hazardous).

3. Threshold Alerts – Sends SMS/Email alerts when noise exceeds safe levels as per WHO or local standards.

4. Historical Data Analysis – Shows noise trends by day, week, or season.

5. Event Impact Analysis – Compares noise levels before, during, and after public events or construction.

6. Predictive Modeling – Uses machine learning to forecast high-noise times in specific locations.

7. Public Awareness Dashboard – Allows residents to check current noise conditions in their area.

8. Mobile-Friendly Access – Works on both desktop and smartphones for field monitoring.

Technology Stack:

• Backend: Node.js / Java / PHP (REST APIs for sensor data processing)

• Frontend: HTML, CSS, Bootstrap, JavaScript (Leaflet.js / Google Maps API for map visualization)

• Database: MySQL / MongoDB (for storing noise level history)

• Data Science Layer: Python (pandas, NumPy, scikit-learn for prediction models)

• IoT Integration: Noise sensors (e.g., Sound Level Meter Modules, MEMS microphones) with microcontrollers like Arduino or ESP8266

Example Use Case:

• In a busy metropolitan city, noise sensors are installed near schools, hospitals, and highways.

• The system shows that a hospital area regularly experiences noise above 80 dB during evening rush hour.

• Authorities use this data to enforce traffic restrictions and install sound barriers.

• During a festival, the platform predicts a 50% spike in noise levels in certain areas and alerts residents in advance.