IoT
Data Science
Web Development
Urban Soundscape Harmonizer
A comprehensive IoT simulation platform for environmental monitoring across major Indian metropolitan areas. Built with modern web technologies and time-series databases for scalable data processing.
Highlights
- Real-time noise analysis system
- Interactive city mapping display
- ML-based prediction algorithms
- Time-series data visualization
Overview
Urban Soundscape Harmonizer is an IoT simulation platform for monitoring and analyzing noise pollution across major Indian metropolitan areas. The system combines real-time data collection with machine learning to predict and visualize urban noise patterns.
Key Features
- Real-Time Noise Analysis: Process audio data from simulated IoT sensors
- Interactive City Maps: Leaflet-based visualization showing noise levels across cities
- ML Predictions: TensorFlow models predicting noise patterns based on time and location
- Time-Series Storage: InfluxDB for efficient storage and querying of sensor data
Technical Stack
React frontend with Leaflet for mapping, FastAPI backend for high-performance API, InfluxDB for time-series data, and TensorFlow for predictive models. Containerized with Docker.
Applications
- Urban planning and zoning decisions
- Identifying noise pollution hotspots
- Measuring impact of traffic management policies
- Public health noise exposure assessment
