🏥 NeuroHeart - Stroke Prediction & IoT System

Welcome to NeuroHeart! This is an intelligent system combining IoT (Internet of Things) and AI (Artificial Intelligence) to monitor cardiovascular health and predict stroke risks in real-time.

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📚 1. System Overview

The system consists of 3 main components working together:

1. IoT Device (Hardware): Measures heart rate and oxygen saturation (SpO2) from the patient and sends data to the Server.
2. Server & AI (The Brain): Receives data, runs the AI model (XGBoost) to analyze risk factors.
3. Client (Web & Zalo): Displays results and sends emergency alerts to relatives/doctors.

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🛠 2. Prerequisites

Before starting, ensure your computer has the following tools:

Basic Software

• Python (version 3.8+): The main programming language.
  • Download: python.org
• VS Code: Code editor.
• Git: Version control tool (to download the project).

Libraries & Auxiliary Tools

• Mosquitto MQTT: Middleware to receive messages from sensors.
• Python Libraries (included in requirements.txt):
  • Flask: Runs the web server.
  • pandas, numpy: Data processing.
  • xgboost, scikit-learn: Runs the AI model.
  • paho-mqtt: MQTT connection.

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💻 3. Installation Guide (Localhost)

How to run the project on your personal computer.

Step 1: Download Source Code

Open Terminal (or CMD/PowerShell) and run:

git clone https://github.com/Wangtran106/NeuroHeart_Project.git
cd NeuroHeart_Project

Step 2: Create Virtual Environment

A virtual environment keeps libraries organized.

# Windows
python -m venv venv
venv\Scripts\activate

# Mac/Linux/Ubuntu
python3 -m venv venv
source venv/bin/activate

(After running, you should see (venv) at the start of your Terminal line)

Step 3: Install Libraries (IMPORTANT)

Run the following command to automatically install all required libraries:

pip install -r requirements.txt

Step 4: Configure Environment Variables

Create a file named .env (with the dot at the beginning) and fill in the following parameters:

# MQTT Configuration (Use Localhost if running locally)
MQTT_BROKER=127.0.0.1
MQTT_PORT=1883
MQTT_USERNAME=wangtran
MQTT_PASSWORD=1006

# Web Configuration
FRONTEND_API_URL=http://127.0.0.1:5000
SECRET_KEY=your-secret-key

Step 5: Run the Project

python app.py

If you see Running on http://127.0.0.1:5000, it is successful! Open your browser and visit that address.

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☁️ 4.Real Server

To put the project online for public access.

🤖 5. Zalo Bot & Hardware

• Zalo Bot: Code located in zalo_module.py. Get ZALO_BOT_TOKEN and add it to .env.
• Sensor (ESP32): Hardware code (Arduino) needs to be flashed separately.

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Author: Tran Dinh Quang Contact: trandinhquang011@gmail.com