| KEYWORD |
Developing a Low-Cost Real-Time Sign Language Recognition Platform Using MicroPython
keywords ARTIFICIAL INTELLIGENCE, DATA SCIENCE, EMBEDDED SYSTEM, MICROCONTROLLER, PYTHON
Reference persons SARAH AZIMI, LUCA STERPONE
Research Groups DAUIN - AEROSPACE AND SAFETY COMPUTING LAB
Thesis type RESEARCH / EXPERIMENTAL, RESEARCH ORIENTED, RESEARCH, INNOVATIVE
Description The use of sign language is essential for individuals who are deaf or hard of hearing, providing a critical tool for communication. However, current automatic sign language recognition platforms are often complex and costly, limiting their ability to be widely used and effectively improve accessibility for this community.
This thesis aims to address this challenge by focusing on the development of a low-cost, real-time sign language recognition platform. The project will utilize the MicroPython programming language, which is a simplified version of Python specifically designed for microcontrollers. MicroPython provides a convenient and accessible way to program small computing devices, such as those used in IoT devices, robotics, and wearable technology.
By leveraging the capabilities of MicroPython and the Pyboard microcontroller module, the thesis will explore state-of-the-art techniques for sign language recognition, with the goal of creating a cost-effective and user-friendly solution for this community. The student will work on Pyboard, a powerful and low-power microcontroller module that runs MicroPython.
Required skills Knowledge on Python
Deadline 01/05/2023
PROPONI LA TUA CANDIDATURA