IoT-Based Online Electronics Lab

Table of Contents

1. Overview
2. Functionality
3. System Architecture
4. Hardware Requirements
5. Software Requirements
6. LRC Values
7. Installation and Setup
   • Dependencies
   • Installing Dependencies
   • Steps
8. Usage
9. Code Structure
10. Troubleshooting
11. Future Improvements
12. License
13. Acknowledgements

Overview

This project implements an IoT-based online electronics lab, allowing students to remotely conduct experiments using real electronic components controlled via a Raspberry Pi 4 server. A Flask web application provides a user interface to control the experiment parameters and visualize the results.

Functionality

1. AC Signal Generation:

   • Students input desired frequency values through the web interface.
   • The Raspberry Pi controls an LM324 operational amplifier to generate an AC signal.
   • The frequency of the AC signal is adjusted using an MCP4131 digital potentiometer.

2. LRC Circuit:

   • The AC signal is passed through an LRC circuit (inductor, resistor, capacitor).
   • The values of L, R, and C are selectable by the user via the web interface.
   • Digital multiplexers (74LS139) are used to switch between different LRC configurations.

3. Signal Amplification:

   • The output signal from the LRC circuit is amplified using a MAX4171 amplifier.

4. Data Acquisition and Visualization:

   • An ADS1115 analog-to-digital converter (ADC) connected to the Raspberry Pi measures the amplified output signal.
   • A Kalman filter is applied to the measured voltage readings to reduce noise.
   • The filtered signal is plotted using Matplotlib.
   • The plot is converted into an image and sent back to the web interface for visualization.

System Architecture

The system comprises the following key components:

• Web Interface (Flask): A Flask-based web application that provides a user interface for students to input experiment parameters (L, R, C values, frequency) and view the results.
• Raspberry Pi 4: Acts as the server, controlling the electronic components based on user input and acquiring data from the ADC.
• MCP4131 Digital Potentiometer: Controls the frequency of the AC signal generated by the LM324.
• 74LS139 Digital Multiplexers: Select the appropriate LRC component values based on user input.
• MAX4171 Amplifier: Amplifies the output signal from the LRC circuit.
• ADS1115 ADC: Converts the analog output signal to a digital signal that can be read by the Raspberry Pi.
• Electronic Components (LM324, R, L, C): The actual electronic components used in the experiment.

Hardware Requirements

• Raspberry Pi 4
• ADS1115 ADC
• MCP4131 Digital Potentiometer
• 74LS139 Digital Multiplexers
• MAX4171 Amplifier
• LM324 Operational Amplifier
• Resistors, Inductors, Capacitors (see LRC Values section below)
• Breadboard, Jumper wires
• Power supply

Software Requirements

• Python 3.7+
• Flask
• Adafruit ADS1x15 library
• RPi.GPIO
• spidev
• Matplotlib
• FilterPy
• NumPy

LRC Values

The following LRC values are available for selection through the web interface. The digital multiplexers are configured to switch between these values.

Inductor Values:

Selection	Value
L1	4.7 µH
L2	10 µH
L3	15 µH
L4	100 µH

Capacitor Values:

Selection	Value
C1	0.33 µF
C2	1 µF
C3	3.3 µF
C4	33 µF

Resistor Values:

Selection	Value
R1	2 kΩ
R2	2.2 kΩ
R3	22 kΩ
R4	100 kΩ

Installation and Setup

Dependencies

The project relies on the following software dependencies:

• Python Packages:
  • Flask
  • Adafruit ADS1x15
  • RPi.GPIO
  • spidev
  • Matplotlib
  • FilterPy
  • NumPy

Installing Dependencies

It is highly recommended to use a virtual environment to manage project dependencies.

1. Create a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate  # On Linux/macOS
   venv\Scripts\activate  # On Windows

2. Install Python dependencies:

   pip install -r requirements.txt

   Create a requirements.txt file with the following:

   Flask
   adafruit-ads1x15
   RPi.GPIO
   spidev
   matplotlib
   filterpy
   numpy
   

Steps

1. Clone the repository:

   git clone [repository URL]
   cd [repository directory]

2. Install Python dependencies: (See "Installing Dependencies" above)

3. Enable SPI interface on Raspberry Pi:

   • Run sudo raspi-config.
   • Select "Interface Options".
   • Enable "SPI".
   • Reboot the Raspberry Pi.

4. Connect the electronic components according to the circuit diagram. Important: Double-check your wiring before powering on the system.

   

5. Run the Python scripts in separate terminals:

   • Terminal 1: python only_ADS_kalman_wth_sliders.py
   • Terminal 2: python only_switching.py
   • Terminal 3: python only_MCP.py

6. Run the Flask web application: (Assuming you have a Flask app file, e.g., app.py)

   python app.py

   Detail the specifics of your Flask application setup here. Include the port it runs on.

Usage

1. Open a web browser and navigate to the address of the Flask web application (e.g., http://<Raspberry Pi IP address>:5000).
2. Enter the desired values for L, R, and C (selecting from the values listed in the LRC Values section), and frequency in the web interface.
3. Click the "Run Experiment" button.
4. The web interface will display the plot of the output signal.

Code Structure

• only_ADS_kalman_wth_sliders.py: Reads analog voltage values from the ADS1115, applies a Kalman filter, and plots the filtered data. Includes sliders to adjust Kalman filter parameters.
• only_switching.py: Controls the digital multiplexers (74LS139) to switch between different LRC configurations based on the selected L, R, and C values.
• only_MCP.py: Controls the MCP4131 digital potentiometer to adjust the frequency of the AC signal.
• app.py (Example): The Flask web application (you'll need to provide your actual Flask app file). This file handles user input, communicates with the other Python scripts, and displays the results.
• requirements.txt: Lists the Python dependencies for the project.

Troubleshooting

• No signal: Check the wiring connections and power supply.
• Incorrect frequency: Verify the MCP4131 settings and the LM324 circuit.
• Incorrect L, R, or C value: Check the wiring to the 74LS139 multiplexers and verify that only_switching.py is correctly configured.
• Noisy signal: Adjust the Kalman filter parameters (R and Q) using the sliders.
• Web application not running: Ensure that Flask is installed correctly and that the app.py script is running without errors.
• SPI Communication Error: Verify that SPI is enabled on your Raspberry Pi and the wiring to the MCP4131 is correct.

Future Improvements

• Implement error handling and input validation in the web interface.
• Add support for different types of experiments.
• Implement a more sophisticated control algorithm for the AC signal generation.
• Develop a user authentication system to restrict access to the lab.
• Create a graphical user interface for calibration of the ADS1115.
• Improve the Kalman filtering by using a state-space model specifically tailored to the noise characteristics of the system.

License

Acknowledgements

We would like to express our sincere gratitude to the following:

• The Python Software Foundation: For developing and maintaining the Python programming language, which is the foundation of this project.
• The Flask Team: For creating the Flask web framework, which enables the creation of the web interface for this online lab.
• Adafruit Industries: For providing the Adafruit ADS1x15 library, which simplifies communication with the ADS1115 ADC.
• The RPi.GPIO Library Developers: For creating the RPi.GPIO library, which allows us to easily control the GPIO pins on the Raspberry Pi.
• The Spidev Library Developers: For the spidev library that enables SPI communication with the MCP4131.
• The Matplotlib Team: For developing Matplotlib, a powerful plotting library used to visualize the output signal.
• The FilterPy Team: For the FilterPy library, which provides Kalman filtering capabilities for noise reduction.
• The NumPy Team: For developing NumPy, a fundamental package for scientific computing with Python.

We also acknowledge the open-source community for their contributions to the libraries and tools used in this project. Their work has been invaluable in making this project possible.