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

Objective

To develop a platform that analyzes attendee emotions during events using facial recognition, voice analysis, or wearable sensors. The system provides insights into audience engagement, satisfaction, and reactions, helping organizers optimize future events and experiences.

Key Features

Feature	Description
User Registration & Login	Organizers create accounts to monitor and analyze events.
Emotion Detection	Use AI/ML to detect attendee emotions (happiness, surprise, boredom, etc.) from live video, audio, or wearable data.
Real-Time Analytics	Display live metrics of audience emotions during the event.
Heatmaps & Visualizations	Visualize emotions across event zones, stages, or audience groups.
Event Recording & Analysis	Store event data for post-event analysis and reports.
Notifications & Alerts	Alert organizers if negative emotions or disengagement spikes occur.
Admin Dashboard	Manage events, review emotion analytics, and generate reports.
Integration with Cameras & Wearables	Connect cameras, microphones, or sensors for emotion detection.
Historical Data Comparison	Compare audience reactions across different events or sessions.

Technology Stack

Frontend (User & Admin): React.js / Angular / Vue.js, Tailwind CSS / Bootstrap

Backend: Node.js (Express) / Django / Spring Boot, REST APIs

AI/ML Layer:

Computer Vision (OpenCV, TensorFlow, or PyTorch) for facial emotion detection
Voice Emotion Recognition using Python libraries or ML models
Sentiment analysis and pattern recognition algorithms

Database: PostgreSQL / MySQL (user & event data), MongoDB (emotion metrics, logs)

Notifications & Alerts: Firebase / Twilio / SendGrid for alerts and notifications

Cloud & Hosting: AWS / Azure / GCP for scalable hosting, storage, and ML model deployment

Workflow

User Registration/Login → Organizers create accounts and configure event settings.
Event Setup → Define event sessions, zones, or audience groups.
Data Collection → Capture live video, audio, or wearable sensor data from attendees.
Emotion Analysis → AI/ML models process the data to detect emotions in real-time.
Visualizations & Heatmaps → Display live dashboards showing emotional trends and intensity across the event.
Notifications & Alerts → Notify organizers if disengagement or negative emotions spike.
Post-Event Analysis → Generate detailed reports comparing sessions, audience engagement, and sentiment trends.
Admin Management → Oversee events, analytics, and AI model performance.

User Roles

Event Organizer → Set up events, monitor real-time emotion analytics, receive alerts, and review reports.
Admin → Manage platform users, AI model configuration, events, and ensure secure data handling.

Security Features

Role-based access control (RBAC)
Secure authentication using JWT / OAuth 2.0
Encrypted storage of video, audio, and sensor data
GDPR-compliant handling of personal and biometric data
Privacy-preserving techniques for sensitive attendee information

Analytics

Real-time audience emotions during sessions
Engagement patterns and peak attention periods
Comparison of audience reactions across multiple events
Identification of zones or segments with higher or lower engagement
Trends for future event planning and improvement

What You Get

AI-powered emotion analytics platform for events
Real-time dashboards and visualizations of attendee emotions
Alerts for engagement drops or negative sentiment
Post-event reporting with actionable insights
Admin controls for event management and analytics monitoring

Why Choose This Project?

Provides actionable insights into audience engagement and satisfaction
Leverages AI/ML for real-time and post-event analytics
Scalable for conferences, concerts, webinars, and public events
Demonstrates integration of full-stack development with computer vision, audio analysis, and data visualization
Helps organizers optimize event experience and decision-making