A REVIEW OF ASSISTIVE NAVIGATION SYSTEMS FOR VISUALLY IMPAIRED PEOPLE: TRENDS, CHALLENGES, AND FUTURE SCOPE

Abstract

Visual impairment is a global issue affecting more than 2.2 billion individuals, significantly limiting independent mobility and safe navigation. Over recent years, numerous assistive technologies have been proposed, including IoT-enabled mobility aids, wearable devices, deep learning-based perception systems, and physiological monitoring approaches. Despite these advancements, current solutions remain fragmented and fail to address real-world navigation comprehensively. This paper reviews a set of representative studies covering diverse approaches such as smart sticks, embedded systems, computer vision-based detection models, and emotion-aware warning mechanisms. A critical analysis reveals seven major research challenges: lack of end-to-end navigation systems, insufficient real-world validation, limited user-centric design, incomplete obstacle detection, absence of adaptive feedback, weak sensor integration, and unresolved ethical concerns. Based on these findings, this paper outlines key research directions for developing robust, scalable, and user-focused assistive navigation systems.