5000+ Computer Science Projects | Degree | Diploma | MCA | BCA

Event, Travel & Ticket Booking
Reviews

Emotion Detection for Event Feedback

Objective

To develop an AI-powered platform that analyzes attendee emotions during and after events using facial recognition, text/speech sentiment analysis, and feedback forms, helping organizers measure audience engagement and satisfaction in real time.

Key Features

Module	Feature
User Module	Login, profile management, event participation
Emotion Capture	Facial expression recognition via webcam/mobile camera during sessions
Sentiment Analysis	Text and voice-based sentiment extraction from post-event feedback
Dashboard (User)	View personal feedback history, sentiment analysis results
Dashboard (Organizer)	Real-time audience emotion dashboard during sessions
Reports & Analytics	Event-level engagement scores, emotion trends, session-wise breakdown
Feedback System	Attendees submit written/audio feedback; system auto-analyzes emotions
Admin Panel	Manage events, sessions, attendees, and reports
Notification	Automated email/SMS updates with feedback summaries

Technology Stack

Layer	Technology Options
Frontend	HTML, CSS, Bootstrap, JavaScript, React / Vue.js
Backend	Python (Flask/Django) / Node.js (Express)
Database	MongoDB / PostgreSQL / MySQL
AI/ML	OpenCV, TensorFlow/Keras, PyTorch, Hugging Face Transformers
Sentiment Analysis	NLTK, TextBlob, VADER, Speech-to-Text APIs
Authentication	JWT / Firebase Auth / OAuth
Hosting	AWS EC2 / Google Cloud / Azure
Other	WebRTC (for camera access), Twilio/SendGrid (for notifications)

Workflow

Emotion Detection Flow

Attendee logs in and joins the event session.
AI model captures live facial expressions via webcam (optional, with consent).
System assigns an emotion score (happy, sad, neutral, engaged, bored).
Feedback form post-event → Text/voice analyzed for sentiment.
Results shown to organizers in real time + stored in reports.

Organizer Flow

Admin/Organizer logs in → dashboard.
Creates event/session → adds attendees.
Views live emotional analytics during event.
Downloads engagement/emotion report after event.

User Roles

Role	Permissions
Attendee	Join events, give feedback, consent for emotion analysis, view personal sentiment history
Organizer	Manage events, access audience emotion dashboard, view/export reports
Admin	Manage all organizers, events, users, and AI system settings

Security Features

JWT-based secure authentication
Role-based access control (Attendee, Organizer, Admin)
Encrypted data storage for user feedback and video frames
Consent-based video analysis (GDPR/Privacy compliance)
CAPTCHA and rate-limiting to prevent spam submissions

Analytics (Organizer Dashboard)

Metric	Description
Emotion Distribution	% of happy, neutral, sad, engaged attendees
Real-Time Trends	Live graph of emotion changes during event
Session Engagement	Engagement score per session/speaker
Sentiment Insights	Breakdown of positive, neutral, negative feedback
Overall Satisfaction Index	Combined score from emotions + feedback

What You Get

AI-powered emotion detection system
Real-time attendee emotion dashboard
Feedback sentiment analysis (text + voice)
Event/session-wise engagement analytics
Admin/Organizer control panel with reports
Email/SMS notification integration

Why Choose This Project?

This project merges AI, sentiment analysis, and event management, making it highly innovative and impactful. It demonstrates expertise in computer vision, natural language processing, machine learning, and full-stack development, while also tackling a real-world problem of measuring attendee engagement. It’s perfect for academic, research, and industry use cases.

This Course Fee: