IOT Based Smart Shoes for Blind Navigation

Abstract

Safe mobility and independent navigation remain major challenges for blind and visually impaired individuals due to their inability to perceive environmental hazards, often resulting in accidents, falls, and disorientation. To address these challenges, this paper presents the design, implementation, and validation of an IoT-enabled smart shoe system aimed at enhancing mobility, safety, and independence for visually impaired users. The proposed system integrates multiple sensing modules, including ultrasonic or infrared sensors for obstacle detection, moisture sensors for wet floor identification, and inertial sensors for fall detection. Sensor data is processed by an embedded microcontroller to accurately identify hazardous situations and distinguish them from normal movements. Upon detecting danger, the system provides real-time voice-based acoustic alerts to inform the user and simultaneously communicates with a dedicated mobile application that shares the user’s location and notifies caregivers during emergencies. Special emphasis is placed on electrical safety, system reliability, and fault tolerance to reduce false alarms and improve accuracy. Experimental evaluation conducted on five subjects under real-world conditions demonstrated high detection performance, with an overall accuracy of approximately 96%, confirming the effectiveness of the proposed system as a reliable assistive technology for visually impaired individuals.

Introduction

The text discusses the development of an IoT-enabled smart shoe system designed to improve the mobility, safety, and independence of visually impaired individuals. Visually impaired people often face difficulties in detecting obstacles, slippery surfaces, and sudden environmental changes, which can lead to accidents, falls, and loss of confidence. Traditional aids such as white canes and guide dogs provide limited environmental awareness and cannot detect elevated obstacles, wet surfaces, or emergency situations.

To address these limitations, the proposed smart shoe integrates multiple sensors, including ultrasonic or infrared sensors for obstacle detection, moisture sensors for wet surface detection, and accelerometers and gyroscopes for fall detection. An embedded microcontroller continuously processes sensor data using predefined algorithms to distinguish between normal and hazardous conditions.

When danger is detected, the system provides immediate voice-based audio alerts, which are considered more informative and user-friendly than vibration feedback. The smart shoe is also connected to a mobile application through IoT technology, allowing caregivers to receive emergency notifications and the user’s live location in real time. The system emphasizes reliability, fault tolerance, and electrical safety for daily use.

The project offers several advantages, including enhanced mobility, real-time hazard detection, remote monitoring, accurate performance, and increased independence for visually impaired users. However, it also has limitations such as higher initial cost, dependence on charging and network connectivity, and reduced performance under extreme environmental conditions.

The literature survey reviews previous research on assistive mobility systems for visually impaired individuals. Existing works include sensor-based navigation aids, smartphone-integrated systems, GPS-based guidance, wearable devices, and IoT-enabled navigation solutions. While these systems improve independence and navigation, common limitations include high power consumption, battery dependency, limited detection accuracy, water sensitivity, bulky designs, and reliance on smartphones. The proposed smart shoe aims to overcome many of these challenges by combining real-time sensing, voice guidance, IoT connectivity, and emergency support into a compact wearable solution.

Conclusion

This work presents the development of an IoT-enabled smart shoe system designed to assist blind and visually impaired individuals in safe navigation. The proposed system integrates multiple sensors, including ultrasonic or infrared sensors for obstacle detection, moisture sensors for wet surface identification, and inertial sensors for fall detection. Sensor data are processed using an embedded microcontroller to generate real-time voice-based alerts, enabling timely user awareness of potential hazards. Furthermore, the system incorporates a mobile application to share location information and notify caregivers during emergency situations. Experimental results demonstrate that the proposed system achieves a high detection accuracy of approximately 96% under real-world conditions, indicating its reliability and effectiveness. The results confirm that the smart shoe system offers a practical, low-cost, and efficient assistive solution to enhance mobility, safety, and independence for visually impaired users.

References

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Copyright

Copyright © 2026 Sanika Kamble, Gayatri Pujari, Pradnya Kamble, Prof. Miss P. P. More. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.