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An Inclusive Offline Learning Platform Integrating Gesture Recognition and Local AI Models
Marius-Valentin Drăgoi1, Ionuț Nisipeanu2, Roxana-Adriana Puiu1
1Faculty of Industrial Engineering and Robotics, National University of Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania.
Biomimetics (Basel, Switzerland)
|October 28, 2025
Summary
This study presents a gesture-controlled interface using local AI for hands-free access to educational materials. It enhances accessibility and interaction through intuitive hand movements, offering a seamless user experience.
Area of Science:
- Human-Computer Interaction
- Artificial Intelligence
- Educational Technology
Background:
- Traditional interfaces require manual input, limiting accessibility.
- Hands-free interaction is crucial for diverse user needs and environments.
- AI advancements enable sophisticated control through natural gestures.
Purpose of the Study:
- To introduce a gesture-controlled conversational interface powered by a local AI model.
- To enhance accessibility and enable hands-free interaction with digital educational content.
- To develop a system for automated content summarization and quiz generation via gestures.
Main Methods:
- Real-time hand gesture recognition using a standard laptop camera.
- Integration with a local AI engine for processing and content generation.
- Development of a unified gesture set for navigation and interaction.
Main Results:
- The system successfully processed documents, generated summaries, and created quizzes using gestures.
- Gesture detection accuracy and low command-response latency were observed.
- User satisfaction indicated a seamless and effective hands-free experience.
Conclusions:
- The gesture-controlled interface offers a significant advancement in accessibility and human-computer interaction.
- The system provides a practical framework for multimodal AI-driven educational aids.
- This technology has strong potential for intelligent interface design and personalized learning.
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