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MoodyPi

An Emotion-Detecting Interactive System by Team MoodyPi


MoodyPi

An Emotion-Detecting Interactive System by Team MoodyPi


About

MoodyPi is an interactive AI project designed to introduce participants to real-world applications of artificial intelligence through emotion detection. The workshop demonstrates how AI can interpret human emotions and respond with real-time feedback.

Participants engage with a live system that captures facial expressions, predicts emotions, and prints personalized messages, making AI concepts tangible and engaging.


Project Information

Difficulty Level: Beginner – Intermediate
Target Audience: K-12 – College
Duration of Workshop: 30–60 minutes

Needed Materials

  • Raspberry Pi
  • Camera Module
  • Thermal Printer
  • Computer (for setup)

Learning Outcomes

  • Understand basic concepts of AI and emotion recognition
  • Experience real-time machine learning applications
  • Learn how hardware and software integrate in AI systems

Main Technology

  • Raspberry Pi
  • TeachableMachine

Team: MoodyPi

  • Nghia Nguyen (Pine)
  • Truman Sok
  • Jumara Sandoval

Advisors

  • Dr. Wei Jin
  • Dr. Xin Xu

Project Description

MoodyPi is a Raspberry Pi–based system that detects human emotions using a camera and a trained machine learning model. When a user interacts with the system, their facial expression is analyzed in real time, and a corresponding message is printed instantly.

The project combines AI, computer vision, and embedded systems to create an engaging and hands-on learning experience.


Outreach

  • TAP Expo
  • Super Saturday Series
  • Classroom Workshops
  • CREATE Symposium

How It Works

  1. The camera captures a live image of the user
  2. The system processes the image using a trained AI model
  3. The model predicts the user's emotion
  4. A message is selected based on the detected emotion
  5. The thermal printer prints the message instantly

Setup / Installation

  1. Connect Raspberry Pi to power
  2. Attach camera module
  3. Connect thermal printer
  4. Install required libraries (OpenCV, TensorFlow Lite)
  5. Run the main Python script

Usage

  1. Stand in front of the camera
  2. Allow the system to detect your emotion
  3. Wait for the printed message
  4. Read your personalized output

Repository Structure

MoodyPi/
├── code/
├── documents/
├── media/
├── resources/
└── README.md

Conclusion

MoodyPi bridges the gap between theory and practice by allowing users to experience AI in real time. It promotes engagement, learning, and curiosity through interactive technology.

About

Spring 2026

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