Review on Advanced Blind Stick Using AI

Visually impaired individuals face significant challenges in safe and independent navigation due to the limitations of conventional white canes, which can only detect nearby obstacles. This paper proposes an Advanced AI-Based Smart Blind Stick that integrates an AI camera, ultrasonic sensors, GPS, hybrid indoor–outdoor navigation, fall detection, and emergency SOS features into a single assistive device. A Raspberry Pi running the YOLOv8 model performs real-time object detection, while an ESP32 manages sensor data and communication modules. The system provides voice guidance, obstacle detection, live location tracking, and automatic emergency alerts to caregivers during critical situations. By combining AI-based vision with sensor fusion and navigation technologies, the proposed solution enhances user safety, mobility, and independence. The system is designed as a low-cost, portable, and efficient assistive device suitable for real-world applications, offering improved performance compared with existing smart blind stick systems.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-26
DOI
https://doi.org/10.5281/zenodo.23663796
Primary Topic
Assistive Technology in Communication and Mobility
Type
article
Field-Weighted Citation Impact
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article

Review on Advanced Blind Stick Using AI

Prof. S. J. Pardeshi, Pogul Chinmay R., Prof. P.P. Melge
Zenodo (CERN European Organization for Nuclear Research)
Assistive Technology in Communication and Mobility
article

Review on Advanced Blind Stick Using AI

Prof. S. J. Pardeshi, Pogul Chinmay R., Prof. P.P. Melge
article en

Abstract

Visually impaired individuals face significant challenges in safe and independent navigation due to the limitations of conventional white canes, which can only detect nearby obstacles. This paper proposes an Advanced AI-Based Smart Blind Stick that integrates an AI camera, ultrasonic sensors, GPS, hybrid indoor–outdoor navigation, fall detection, and emergency SOS features into a single assistive device. A Raspberry Pi running the YOLOv8 model performs real-time object detection, while an ESP32 manages sensor data and communication modules. The system provides voice guidance, obstacle detection, live location tracking, and automatic emergency alerts to caregivers during critical situations. By combining AI-based vision with sensor fusion and navigation technologies, the proposed solution enhances user safety, mobility, and independence. The system is designed as a low-cost, portable, and efficient assistive device suitable for real-world applications, offering improved performance compared with existing smart blind stick systems.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 5%
Assistive Technology in Communication and Mobility
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