Software Systems & Electronics Integration for the Javelin Jr. NJITRC Fall 2024 Launch

Overview

This project is designed to support data collection and transmission using a RYLR998 LoRa radio module in a rocket system. The system is integrated with a Flask web application that allows real-time data visualization and control via a web interface. The RYLR998 module is responsible for sending and receiving data, and the Flask web app manages communication with the module and provides a visual display of the transmitted data.

Table of Contents

• System Design
• Features
• Code Structure
• Installation
• Usage
• Contributors
• License

Features

• Data Collection - Collects sensor data from the LoRa module and sends it to the Flask server for visualization.
• Flask Web Interface - Allows users to initiate data collection and visualize data through WebGL.
• Socket Communication - Real-time communication between the Flask server and the front-end using Flask-SocketIO.
• Password Authentication - Ensures that data collection can only start with the correct password.
• WebGL Visualization - Displays the received data in real-time using WebGL on the front-end.
• LoRa Data Transmission - Encodes and sends quaternion data over the LoRa radio module.
• Quaternion Based Interpolation - Responsible for silky smooth rotational animations, massively improves framerate
• Livetime Visualization - Utilizes WebGL to visualize

Code Structure

The project is structured into the following key files:

• altimeter.py: Manages altitude measurement and data processing for the LoRa module.
• camera.py: Handles video capture and logging from a Raspberry Pi camera module, supporting non-blocking video recording.
• recieve.py: Receives and decodes data from the LoRa module.
• quaternion.html: Abstracts quaternion mathematics for zeroing upon calibration
• metrics.py: Provides functions for processing telemetry data, including time delta and quaternion encoding/decoding.
• requirements.txt: Lists the Python dependencies required for the project.
• transmit.py: Encodes and transmits data to the LoRa module.
• index.html: The homepage of the web application for password authentication.
• visualize.html: Displays real-time visualizations of the transmitted data.
• .env: Contains environment variables, including the hashed password for authentication.
• RPI02W.py: Manages interaction with the Raspberry Pi 2W for telemetry and sensor data collection.
• RP15.py: Runs the Flask server and handles socket communication for password validation and real-time data emission.

Installation

1. Clone this repository to your local machine:

   git clone https://github.com/your-repo/javelin-jr.git

2. Install the necessary Python dependencies:

   pip install -r requirements.txt

3. Set up the environment variables by creating a .env file in the root directory:

   hashedPassword=<your_hashed_password>

4. Ensure the RYLR998 LoRa module is connected and properly configured.

Usage

After installation and configuration, start collecting and logging flight data with the following command:

python RP102W.py

Once the system is installed and configured, start the Flask application by running the following command:

python RP15.py

Contributors

The following individuals have contributed to this project's software:

• Matthew Tujague - Lead Software Engineer/Avionics Manager
• Victor Jimenez - Quaternion-based Interpolation Tech.
• Eric Zhang - Visualization Specialist
• Ryan Ramos - Visualization Specialist
• Amogh Karee - Flask Web Developer
• Matthew Tolocka - Software Optimization Specialist
• Nick C Volpe - Support Engineer

These are the current contributors to the project.

License

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