🎯 𝕊𝕋ℝ𝔼𝕊𝕊 𝔻𝔼𝕋𝔼ℂ𝕋𝕀𝕆ℕ 𝔽𝕆ℝ 𝕀𝕋 𝔓ℝ𝕆𝔽𝔼𝕊𝕊𝕀𝕆ℕ𝔸𝕃𝕊 🧠

An AI-powered wellness ecosystem designed to monitor, detect, and mitigate stress in the high-pressure technology industry.

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📘 1. Project Overview

In the modern IT landscape, chronic stress often leads to burnout. This project provides a proactive monitoring system that transforms digital behavior (typing speed, screen time) and biometric data (heart rate, sleep) into actionable mental health insights. It features an integrated AI Chatbot for real-time support and a comprehensive Analytics Dashboard for both developers and managers.

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🎨 2. System Architecture & Diagrams

🗺️ Activity Flow

Shows the user journey from login to receiving personalized recommendations.

🏗️ Class Architecture

The core data structure and relationships between users, stress patterns, and AI predictions.

📈 Communication Flow

Interaction between system components for stress detection.

🌐 Deployment Model

Physical infrastructure involving Django web servers, Rasa AI servers, and cloud databases.

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✨ 3. Key Features

• 🔍 Multi-Modal Stress Tracking: Monitoring via Keyboard activity, Screen time classification, Voice pitch analysis, and Wearable data (Heart Rate/Sleep).
• 🤖 Conversational AI (Rasa): A empathetic chatbot providing immediate mindfulness exercises and stress-reduction tips.
• ⚖️ ML Anomaly Detection: Uses Isolation Forest and DBSCAN to identify unusual stress-triggering habits.
• 📊 Personalized Dashboards: Interactive charts and health scores for professionals.
• 🔔 Real-time Alerts: Automatic notifications triggered by high-stress behavioral patterns.
• 📚 Resource Hub: Curated library of mindfulness videos, research papers, and articles.

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🚀 4. Installation & Setup

Prerequisites

• Python 3.9 (3.8+ supported)
• Git
• PowerShell (Windows) or bash (Linux/macOS)

Quick Setup Guide

1. Clone the Repository:

   git clone https://github.com/suragsunil/STRESS-DETECTION-FOR-IT-PROFESSIONALS.git
   cd STRESS-DETECTION-FOR-IT-PROFESSIONALS/strees_dection

2. Environment Setup:

   python -m venv venv
   .\venv\Scripts\Activate.ps1   # Windows PowerShell
   # venv\Scripts\activate.bat    # Windows CMD
   # source venv/bin/activate    # Linux/Mac

3. Install Dependencies:

   pip install --upgrade pip
   pip install -r requirements.txt

4. Database Migration:

   python manage.py migrate
   python manage.py collectstatic --noinput   # optional, for static files

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▶️ 5. Running the System

Run these three services in separate terminals (all from the strees_dection directory):

Terminal	Service	Command
1	Django Web App	python manage.py runserver (activate venv first)
2	Rasa Action Server	rasa run actions --port 5055
3	Rasa Core API	rasa run --enable-api --cors "*" --port 5005

Windows: You can use the batch files: start-django.bat, start-rasa-actions.bat, start-rasa-core.bat.

URL	Service
http://127.0.0.1:8000	Django web app
http://localhost:5005	Rasa API
http://localhost:5055	Rasa actions

📖 Detailed run guides: HOW-TO-RUN-DJANGO.md · HOW-TO-RUN-RASA.md · HOW-TO-RUN.md (full system)

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🛠️ 6. Tech Stack

• Backend: Django, REST Framework
• AI/ML: Scikit-Learn, Rasa, Librosa (Audio), Pandas, NumPy
• Frontend: HTML5, Vanilla CSS (Premium Glassmorphism), JavaScript
• Database: SQLite (SQL)

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🎌 7. Conclusion

This project moves mental health support from reactive to preventative. By bridging the gap between digital activity and psychological well-being, we empower IT professionals to lead healthier, more balanced tech careers.

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👤 8. About the Founder

Surag M S
Founder of AI-Powered Stress Detection for IT Professionals

• GitHub: @suragms
• Portfolio: suragsunil.github.io
• LinkedIn: in/suragsunil

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💡 “Helping IT professionals stay mentally healthy — one insight at a time.”