Hybrid Assistive Technologies for Enhancing Accessibility for Visual and Cognitive Impairments

The integration of assistive technologies for individuals with visual and cognitive impairments, such as blindness and Alzheimer's disease, represents a significant advancement in fostering independence and improving quality of life. This document explores the development of a hybrid tool that combines artificial vision systems with cognitive assistance features, along with daily routine reminders. The proposed system utilizes state-of-the-art computer vision technologies, including facial recognition and optical characterrecognition (OCR), to create an artificial visual interface. Additionally, it incorporates cognitive support mechanisms to aid individuals with Alzheimer's in recognizing familiar faces and objects, thereby enhancing memory recall and orientation. By employing a web camera mounted on portable devices, the system identifies faces, detects objects, and converts text into speech, while also providing sign-to-speech conversion for enhanced communication. Furthermore, the system incorporates a daily routine reminder feature, utilizing an Arduino microcontroller, LCD display, and buzzer to prompt users to take medication, consume food, or drink water at specified times. This hybrid tool aims to address the dual challenges faced by individuals with visual and cognitive impairments, promoting inclusivity and reshaping their interactions with the environment.The project utilizes Python for software development, leveraging libraries such as LPBH and Haar Cascade for face recognition, Tesseract for OCR, and pre-trained models for object detection. The integration of sign-to-speech conversion and audio output further enhances the system's functionality. This comprehensive solution not only empowers users but also contributes to the broader goals of accessibility and inclusivity.