LIPO Battery SOH AND RUL

Great! Below is the updated README file, highlighting the use of Flask for the application backend.

Real-Time Battery Monitoring System

Table of Contents

• Introduction
• Features
• Architecture
• Technologies Used
• Installation
• Usage
• Contributing
• License
• Contact
• UI Sample

Introduction

The Real-Time Battery Monitoring System is designed to effectively obtain real-time battery data, estimate battery life, and monitor charging and discharging times using machine learning, IoT devices, and applications. The system consolidates all relevant data and displays it in a user-friendly interface. This project aims to provide accurate and actionable insights into battery performance, ensuring optimal usage and longevity.

Features

• Real-Time Data Acquisition: Continuously collect battery data using IoT sensors.
• Battery Life Estimation: Utilize machine learning algorithms to predict battery life based on historical and real-time data.
• Charging and Discharging Monitoring: Track and estimate charging and discharging times accurately.
• User Interface: Display all collected data and insights through an intuitive and interactive UI.

Architecture

The system architecture is divided into three main components:

1. IoT Devices:

   • Sensors and microcontrollers to collect battery data.
   • Communication modules to transmit data to the server.

2. Backend:

   • Flask server to receive and process data.
   • Machine learning models for estimating battery life and monitoring charging/discharging times.
   • Database to store historical and real-time data.

3. Frontend:

   • Web application to display data, graphs, and insights.
   • Interactive UI designed using Figma (design available here).

Technologies Used

• Programming Languages: Python, JavaScript
• IoT Devices: Arduino, Raspberry Pi
• Machine Learning: Scikit-learn, TensorFlow
• Backend: Flask
• Database: MySQL, MongoDB
• Frontend: React, HTML, CSS
• Design Tools: Figma

Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/battery-monitoring-system.git
   cd battery-monitoring-system

2. Backend Setup:

   • Install Python dependencies:

     pip install -r requirements.txt

   • Start the Flask server:

     python app.py

3. Frontend Setup:

   • Navigate to the frontend directory:

     cd frontend

   • Install dependencies:

     npm install

   • Start the React application:

     npm start

4. IoT Device Setup:

   • Upload the Arduino/Raspberry Pi code from the iot_devices directory to your respective devices.

Usage

1. Deploy IoT Devices: Place the IoT devices near the batteries to collect data.
2. Start Backend and Frontend Servers: Ensure the servers are running.
3. Access the Web Application: Open your browser and navigate to http://localhost:3000 to view real-time battery data and insights.
4. Monitor Battery Performance: Use the interactive UI to analyze battery life, charging, and discharging times.

Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature-branch).
5. Open a Pull Request.

UI Sample

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Thank you for using the Real-Time Battery Monitoring System! We hope it helps you manage and optimize your battery usage effectively.