Integration of Smart Cane with Social Media: Design of a New Step Counter Algorithm for Cane

Author:

Messaoudi Mohamed Dhiaeddine1ORCID,Menelas Bob-Antoine J.1ORCID,Mcheick Hamid1ORCID

Affiliation:

1. Department of Computer Sciences and Mathematics, University of Quebec at Chicoutimi, Chicoutimi, QC G7H 2B1, Canada

Abstract

This research introduces an innovative smart cane architecture designed to empower visually impaired individuals. Integrating advanced sensors and social media connectivity, the smart cane enhances accessibility and encourages physical activity. Three meticulously developed algorithms ensure accurate step counting, swing detection, and proximity measurement. The smart cane’s architecture comprises the platform, communications, sensors, calculation, and user interface layers, providing comprehensive assistance for visually impaired individuals. Hardware components include an audio–tactile interaction module, input command module, microphone integration, local storage, step count module, cloud integration, and rechargeable battery. Software v1.9.7 components include Facebook Chat API integration, Python Facebook API integration, fbchat library integration, and Speech Recognition library integration. Overall, the proposed smart cane offers a comprehensive solution to enhance mobility, accessibility, and social engagement for visually impaired individuals. This study represents a significant stride toward a more inclusive society, leveraging technology to create meaningful impact in the lives of those with visual impairments. By fostering socialization and independence, our smart cane not only improves mobility but also enhances the overall well-being of the visually impaired community.

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

MDPI AG

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