IoT

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.

Urban Soundscape Harmonizer
React FastAPI InfluxDB TensorFlow Leaflet Python Docker

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

Interested in This Work?

Let's discuss how we can collaborate or apply similar techniques to your problems.