eWE-Share

An electric vehicle charging community cross-platform mobile application that predicts the most appropriate charging location according to user needs using machine learning.

Features

• Predicts the best charging location based on user preferences.
• Frontend built with Ionic.
• Backend powered by Flask (located in the flask-server folder).
• Arduino integration for monitoring power usage and energy consumption.

Installation

1. Clone the repository:

   git clone https://github.com/thathsaranandun/eWE-share.git
   cd eWE-share

2. Navigate to the client folder and install dependencies:

   cd client
   npm install

3. Navigate to the Flask server and install dependencies:

   cd ../flask-server
   pip install -r requirements.txt

4. Start the Flask server:

   python app.py

5. Start the Ionic client:

   cd ../client
   ionic serve

Usage

• Open the Ionic application to view charging locations.
• The system predicts the best location using machine learning.
• Arduino modules provide real-time power consumption updates.

Technologies Used

• Ionic (Frontend)
• Flask (Backend)
• Machine Learning (Prediction Algorithm)
• Arduino (Power Monitoring)

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For inquiries or contributions, feel free to open an issue or contact me!