ESP32 IoT Noise Monitor

Overview

The ESP32 IoT Noise Monitor is a sophisticated environmental monitoring solution that measures ambient noise levels in real-time. The system provides continuous sound level monitoring with cloud connectivity for data logging and analysis through ThingSpeak integration.

Features

The system provides comprehensive noise monitoring capabilities including:

• Real-time sound level measurement in decibels (dB)
• High-precision audio sampling using INMP441 I2S microphone
• Live data visualization via OLED display
• WiFi connectivity for remote monitoring
• Cloud data logging through ThingSpeak
• Rolling average calculations (1-minute and all-time)
• Visual status indicators for connectivity and operation

Hardware Requirements

Core Components

• ESP32 Development Board
• INMP441 I2S MEMS Microphone
• SSD1306 OLED Display (128x64)

Pin Configuration

INMP441 Microphone

• WS (Word Select/LRCLK): GPIO 15
• SD (Serial Data): GPIO 13
• SCK (Serial Clock): GPIO 2

OLED Display

• MOSI: GPIO 23
• CLK: GPIO 18
• DC: GPIO 16
• CS: GPIO 5
• RESET: GPIO 17

Software Dependencies

The project relies on the following libraries:

#include <Arduino.h>
#include <driver/i2s.h>
#include <WiFi.h>
#include "ThingSpeak.h"
#include <Wire.h>
#include <Adafruit_GFX.h>
#include <Adafruit_SSD1306.h>

Installation

1. Clone this repository
2. Install PlatformIO in your development environment
3. Create a secrets.h file with your credentials:

#define SECRET_WIFI_NAME "your_wifi_ssid"
#define SECRET_WIFI_PASSWORD "your_wifi_password"
#define SECRET_myChannelNumber your_channel_number
#define SECRET_myApiKey "your_api_key"

4. Configure the project in PlatformIO
5. Upload the code to your ESP32

Configuration

Audio Sampling Parameters

#define SAMPLE_RATE 44100
#define REFERENCE_LEVEL 8192.0
#define SCALE_FACTOR 2.5
#define DB_THRESHOLD 60.0

Display Settings

#define SCREEN_WIDTH 128
#define SCREEN_HEIGHT 64

Operation

The system operates through several key stages:

1. Initialization

   • Configures I2S interface for audio sampling
   • Initializes OLED display
   • Establishes WiFi connection
   • Sets up ThingSpeak client

2. Main Operation

   • Samples audio data continuously
   • Calculates real-time dB levels
   • Updates rolling averages
   • Displays current readings and status
   • Uploads data to ThingSpeak

3. Data Display

   • Current dB level
   • Noise level status (HIGH/LOW)
   • Connection status indicators
   • Rolling averages (1-minute and all-time)

Data Analysis

The system calculates several metrics:

• Instantaneous dB levels
• One-minute rolling average
• Overall average since startup
• Threshold-based noise level classification

ThingSpeak Integration

Data is uploaded to ThingSpeak for long-term storage and analysis:

1. Connects to ThingSpeak server
2. Uploads dB readings every sampling cycle
3. Provides visual confirmation of successful uploads
4. Maintains error handling for failed uploads

Troubleshooting

Common issues and solutions:

1. WiFi Connection Issues

   • Check network credentials
   • Verify network stability
   • Monitor WiFi status indicator on display

2. Sensor Reading Issues

   • Verify I2S connections
   • Check microphone orientation
   • Ensure proper power supply

3. Display Problems

   • Verify I2C connections
   • Check display address configuration
   • Monitor serial output for errors

Development

To modify or extend this project:

1. Fork the repository
2. Make your changes
3. Test thoroughly
4. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Developed by Gonzalo Novoa

Acknowledgments

• ThingSpeak for cloud data storage
• Adafruit for display libraries
• ESP32 community for I2S implementation examples

For additional information or support, please open an issue in the repository.

Publication

The article presents the development and testing of this ESP32-based IoT device for noise monitoring in non-industrial contexts, demonstrating its effectiveness for environmental sound level measurement and real-time data collection through cloud integration. This IoT noise monitoring device has been documented and validated in a peer-reviewed academic publication:

Research Article

Title: Prototipo de dispositivo de IoT para monitoreo del ruido en contextos no industriales

Authors: Y. Castro-Cely, G. R. Novoa-Fernández, B. R. Aragón-Rentería, y M. A. Espitia-Pineda

Journal: Salud, Trabajo y Sostenibilidad (Consejo Colombiano de Seguridad)

Publication Details:

• Volume: 2, Issue: 1
• Pages: 43–55
• Date: July 2025
• DOI/URL: https://publicaciones.ccs.org.co/index.php/sts/article/view/16

IEEE Citation Format

Y. Castro-Cely, G. R. Novoa-Fernández, B. R. Aragón-Rentería, y M. A. Espitia-Pineda, 
«Prototipo de dispositivo de IoT para monitoreo del ruido en contextos no industriales», 
Salud, Trabajo y Sostenibilidad (Consejo Colombiano de Seguridad), vol. 2, n.º 1, pp. 43–55, jul. 2025.