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IV Drip Monitoring System This project is a real-time IV Drip Monitoring System designed to track IV bag levels and alert medical staff. It features a Flask-based backend, a real-time frontend using Socket.IO, and a Python-based simulator for testing.

Features Real-time Monitoring: Uses Socket.IO to push live sensor updates from hardware to the dashboard.

REST API: Exposes endpoints for managing patient records and retrieving historical logs.

Premium UI: A high-contrast, kinetic interface built with CSS (inspired by the "Voldog" aesthetic), GSAP animations, and custom interactions.

Simulated Data: Includes a test_sensor.py script to simulate real-time ESP32 sensor traffic.

Project Structure app.py: Flask backend managing API routes and WebSocket communication.

database.py: SQLAlchemy database models for Patient and SensorLog.

index.html: The main dashboard entry point.

script.js: Handles frontend logic, including tab navigation, card rendering, and real-time animations.

style.css: Premium CSS styling, animations, and responsive layout.

test_sensor.py: Python simulator script for testing the backend with fake sensor data.

requirements.txt: Project dependencies.

Setup and Installation

  1. Prerequisites Ensure you have Python installed.

  2. Install Dependencies pip install -r requirements.txt

  3. Running the Application Start the Flask backend: python app.py

  4. Running the Sensor Simulator (Optional) To see the system react to live data while the backend is running, open a new terminal and run: python test_sensor.py

Technology Stack Backend: Flask, Flask-SocketIO, Flask-SQLAlchemy

Database: SQLite

Frontend: HTML5, CSS3, JavaScript (ES6+), GSAP (Animations)

Production: Gunicorn, Eventlet

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2nd Sem Mini Project which helps in monitoring and controlling the IV Drip Flow

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  • CSS 28.6%
  • JavaScript 22.7%
  • HTML 18.6%
  • Python 18.1%
  • C++ 12.0%