An IoT-Enabled Smart Assistive System for Autonomous Navigation and Environmental Interaction for the Visually Impaired
Abstract
Independent navigation remains a critical challenge for the visually impaired, with existing assistive technologies often limited by computational constraints and poor real-time performance.This paper proposes an IoTenabled smart assistive system that integrates lightweight YOLO-based deep learning models for autonomous obstacle detection, path planning, and environmental interaction.Deployed on edge devices (Raspberry Pi 5, NVIDIA Jetson Nano), the system employs optimized YOLOv8n/YOLOv5s variants with INT8 quantization, achieving 92% mAP@0.5 on custom visually impaired datasets while maintaining >35 FPS inference at
Fields of Study & Subjects
Tactile and Sensory Interactions
Gaze Tracking and Assistive Technology
Assistive Technology in Communication and Mobility
Publication details
- Journal / source
- IARJSET
- Publisher
- Tejass Publishers
- Volume
- 13
- Issue
- 2
- Publication date
- 20 February 2026