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Fruit Ripening Monitoring System Using ESP8266 and VOC Sensors

Table of Contents

Overview

This project aims to monitor and analyze the relationship between various gases and fruit ripening. We use an ESP8266 NodeMCU microcontroller with SGP30, HTU21, and SHT20 sensors to gather data on VOC gases, CO2, H2, ethanol, temperature, and humidity. The collected data is sent to a Python server via WebSocket, which can handle multiple clients simultaneously. The data is stored in an SQLite database, cleaned, and prepared for future data mining to find correlations between the gases and fruit ripening.

image

Features

  • Real-time monitoring:

    • Continuous data collection on VOC gases, temperature, and humidity.
    • SGP30 sensor captures VOC gas concentrations.
    • HTU21 and SHT20 sensors measure temperature and humidity.

  • Multiple sensor modules:

    • Multiple ESP8266 NodeMCU microcontrollers gather data under different conditions.
    • Each microcontroller sends data to the central server.

  • Data communication and storage:

    • Real-time data transfer via WebSocket.
    • Python server handles multiple client connections.
    • Data stored in an SQLite database.

  • Data cleaning and preprocessing:

    • Scripts ensure the dataset is free of errors and inconsistencies.
    • Preprocessing includes handling missing values and outlier detection.

  • Future work:

    • Data mining to identify correlations between gas concentrations and fruit ripening.
    • Use advanced analysis techniques and visualizations.

Usage

  1. Assemble the hardware: Connect the SGP30, HTU21, and SHT20 sensors to the ESP8266 NodeMCU.
  2. Upload the Arduino sketch: Use the Arduino IDE to upload main.ino to the ESP8266.
  3. Start the Python server: Run server.py to start the server.
  4. Begin data collection: The sensors will start collecting data and sending it to the server, which will store it in the SQLite database.

Setup

Arduino Setup

  1. Install Arduino IDE

    • Manjaro: flatpak install cc.arduino.IDE2
    • Windows/Mac: Download from the official website.

  2. Install ESP8266 Board Package

    • Go to File > Preferences in the Arduino IDE.
    • Enter the following URL in the "Additional Boards Manager URLs" field: 
      http://arduino.esp8266.com/stable/package_esp8266com_index.json
    • Click "OK".
    • Open the Boards Manager from Tools > Board > Boards Manager.
    • Search for "ESP8266" and install the "ESP8266 by ESP8266 Community" package.
    • Select the appropriate board from Tools > Board (e.g., NodeMCU 0.9).

  3. Install Required Libraries

    • Go to Sketch > Include Library > Library Manager.
    • Search for and install the following libraries:
      • AVision_ESP8266 by A-Vision
      • ArduinoJson by Benoit Blanchon
      • Adafruit SGP30 Sensor by Adafruit

Python Server Setup

  1. Install Python

    • Manjaro: sudo pacman -S python
    • Windows/Mac: Download from the official website.

  2. Install Python Websockets

    • Manjaro: sudo pacman -S python-websockets
    • Windows/Mac: pip install websockets
    • pip:
    python -m venv myenv
source myenv/bin/activate
pip install --upgrade pip
pip install websockets pandas matplotlib scipy

  3. Run Python Server

    • Execute pythonServer.py to start the server.

Wiring and Connections

To set up the hardware, follow the wiring diagram below. This diagram shows how to connect the ESP8266 NodeMCU microcontroller to the SGP30, HTU21DF, and SHT20 sensors using the SDA and SCL ports. It also includes connections for two LEDs that indicate server connection status and data receiving status.

Wiring Diagram

Connections

  • ESP8266 NodeMCU to SGP30 Sensor:

    • VIN to 3V3
    • GND to GND
    • SCL to D1 (SCL)
    • SDA to D2 (SDA)

  • ESP8266 NodeMCU to HTU21DF Sensor:

    • VIN to 3V3
    • GND to GND
    • SCL to D1 (SCL)
    • SDA to D2 (SDA)

  • ESP8266 NodeMCU to SHT20 Sensor:

    • VIN to 3V3
    • GND to GND
    • SCL to D1 (SCL)
    • SDA to D2 (SDA)

  • LED Indicators:

    • Server connection LED:
      • Positive to D5
      • Negative to GND
    • Data receiving LED:
      • Positive to D6
      • Negative to GND

Report Images

  • Banana Ripening Images:

    Day 1 (11 Nov)
    Day 1

    Day 2 (12 Nov)
    Day 2

    Day 3 (13 Nov)
    Day 3

    Day 4 (14 Nov)
    Day 4

    Day 5 (15 Nov)
    Day 5

    Day 6 (16 Nov)
    Day 6

  • Data Correlation Charts:

    Gas correlation charts from 11 Nov to 16 Nov (the black line indicates when the banana was in perfect shape).

    VOC hourly chart
    VOC

    CO2 and VOC hourly chart
    CO2

    H2 and VOC hourly chart
    H2

    Ethanol and VOC hourly chart
    Ethanol

    Temperature and VOC hourly chart
    Temperature

    Humidity and VOC hourly chart
    Humidity

Future Work

  • Data Mining: Analyze the cleaned dataset to find correlations between VOC gases and fruit ripening.
  • Visualization: Develop visualizations to better understand the relationship between gas levels and the ripening process.
  • Optimization: Improve the accuracy and efficiency of data collection and analysis.

Conclusion

This project provides a robust system for monitoring and analyzing fruit ripening using VOC gas sensors and temperature/humidity sensors. The collected data can be used for further analysis to uncover valuable insights into the ripening process.