Smart Solutions for Visual Impairment by AI-Based Assistive Devices

This paper offers a systematic review on assistive technologies developed for individuals with visual impairments. The review explores a variety of approaches, including wearable devices, computer vision, deep learning, and edge computing, to enhance accessibility and independence for visually impaired users. Each study's methodologies, findings, and limitations are thoroughly examined to provide a comprehensive overview of the latest advancements in this field. The analysis underscores how wearable devices are becoming increasingly advanced, integrating sensors and AI to deliver real-time assistance. Computer vision techniques are being utilized to interpret visual information, which is then conveyed to the user through auditory or haptic feedback. The integration of deep learning and edge computing is also discussed, focusing on how these technologies enhance the accuracy and speed of assistive tools, enabling more responsive and efficient systems. However, the review also identifies several challenges, such as the need for more robust algorithms that can operate in diverse and unpredictable environments, as well as the importance of user-centered design to ensure these technologies are accessible and practical for daily use. The paper concludes by outlining potential areas for future research, emphasizing the need for interdisciplinary collaboration to further refine and expand these technologies. By synthesizing the findings from multiple studies, this review provides valuable insights for researchers and developers working to advance assistive technologies for the visually impaired.