IOT Based Perception Assistive Device for Visually Impaired Using AI

This document The goal of visual implants is to create artificial vision that can partially restore function. It can enhance the quality of life for visually challenged individuals by allowing them to experience light, even after years of darkness, by the use of 60 microelectrodes implanted in the retina. The artificial vision that is made possible by current visual system stimulators has very low resolution because of their small number of microelectrodes. Numerous researchers have sought to enhance artificial vision produced by low-resolution implants through the application of machine learning and image processing techniques. Because phosphine images have low resolution, users report unhappiness with the Retinal Prosthesis System. This underscores the important need for targeted research aimed at improving visual clarity and user pleasure in general. This study presents a novel system that uses voice-based help and real-time dynamic obstacle detection to improve the freedom and safety of blind people when navigating. The system creates a comprehensive and context-aware indoor environment by combining RFID-based pre-implemented tags with sophisticated indoor mapping and semantic mapping technologies. This system’s indoor map editor converts building structures into a digital format by parsing geometric information from architectural models. Semantic mapping uses this digital representation as its foundation and is enhanced with RFID-based tags that offer crucial contextual data such room names, exit points, and landmarks. By guaranteeing that the visually impaired user has access to pertinent spatial data, this semantic mapping improves interior navigation and orientation for the visually impaired user. The system’s capacity to detect dynamic obstacles in real-time is one of its primary features. The system continuously scans the environment to identify moving items or obstacles in the user’s path using a combination of sensors, cameras, and machine learning algorithms. The technology ensures the user’s safety during navigation by detecting objects and instantly adjusting the intended navigation path to avoid collisions. The system incorporates voice-based help to offer simple and easy-to-use interface.