  People with visual impairments face numerous challenges when interacting with
their environment. Our objective is to develop a device that facilitates
communication between individuals with visual impairments and their
surroundings. The device will convert visual information into auditory
feedback, enabling users to understand their environment in a way that suits
their sensory needs. Initially, an object detection model is selected from
existing machine learning models based on its accuracy and cost considerations,
including time and power consumption. The chosen model is then implemented on a
Raspberry Pi, which is connected to a specifically designed tactile device.
When the device is touched at a specific position, it provides an audio signal
that communicates the identification of the object present in the scene at that
corresponding position to the visually impaired individual. Conducted tests
have demonstrated the effectiveness of this device in scene understanding,
encompassing static or dynamic objects, as well as screen contents such as TVs,
computers, and mobile phones.
