FURI | Spring 2022
Assistive Technology for the Visually Impaired for Navigating Cluttered Environments
Several assistive devices and products have been made available in the market in the past few years for the visually impaired. These devices provide feedback to the user through senses such as audio, tactile and haptics. However, most of them lack a comprehensive solution spanning object recognition, text recognition, haptic feedback, and depth mapping, and tend to be expensive. This research explores a combination of various inexpensive existing technologies driven by advances in open-source machine-learning tools for visual analysis. Our goal is to develop a scaled-down model using machine learning on edge devices such as the Raspberry Pi and the Arduino microcontroller.
Hometown: Tempe, Arizona, United States
Graduation date: Spring 2024