Visual Impairment Spatial Awareness System for Indoor Navigation and Daily Activities

Area of Science:

• Computer Science
• Human-Computer Interaction
• Assistive Technology

Background:

• Artificial intelligence (AI) integration enhances autonomy for visually impaired individuals.
• Existing assistive technologies often lack holistic support for indoor activities.

Purpose of the Study:

• Introduce the Visual Impairment Spatial Awareness (VISA) system for comprehensive indoor assistance.
• Enhance spatial awareness, navigation, and object interaction for visually impaired users.

Main Methods:

• Multi-level approach: AR markers for positioning, neural networks for object detection/tracking, depth data for localization.
• Intermediate level: Navigation (obstacle avoidance, pathfinding).
• Advanced level: Synthesized data for enhanced spatial awareness and item location, utilizing text-to-speech and speech-to-text for HMI.

Main Results:

• VISA system demonstrated efficient indoor navigation and object detection/localization.
• Enabled accurate label and text recognition.
• Users interacted naturally with minimal effort in simulated environments.

Conclusions:

• The VISA system significantly enhances spatial awareness and independence for visually impaired individuals.
• The multi-level approach effectively addresses complex indoor navigation and interaction challenges.
• AI-powered assistive technology offers a promising pathway for improving the quality of life for the visually impaired.