Authors : Thanh Tuan Ton That; Khang Huy Ngo; Nam Hien Cao Nguyen

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/yauw3yy8

Scribd : https://tinyurl.com/36kf42kf

DOI : https://doi.org/10.38124/ijisrt/26feb637

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Visual impairment and age-related decline significantly affect independent mobility and safety in daily life. This paper presents a smart monitoring and assistance system aimed at supporting visually impaired individuals and elderly people through the integrating of artificial intelligence, computer vision, and sensor-based technologies. Getting inspired by the working mechanism of the human eye, the proposed system employs the YOLO11 deep learning model for real-time object detection and classification, combined with the Depth Anything v2 model for monocular depth estimation to calculate the distance between users and surrounding objects. The system is implemented using an embedded camera and IoT-based sensors, including ultrasonic distance sensors, GNSS positioning, heart rate monitoring (MAX30102), and fall detection modules, enabling comprehensive environmental perception and user health monitoring. Experimental evaluations were conducted in both bright and low-light environments using a self- collected dataset. The results depict that the proposed system achieves an overall the accurate of detection – approximately 95 percent, with stable performance across varying lighting conditions. The findings confirm the feasibility and effectiveness of integrating deep learning models with embedded hardware to provide real-time assistance. This system has strong potential for development into a wearable smart device capable of enhancing mobility, reducing collision risks, and improving the independence and quality of life for visually impaired and elderly users. Moreover, the proposed approach contributes to the advancement of human-centered intelligent assistive technologies with meaningful social impact.

Keywords : Assistive Technology, Visual Impairment, Elderly Care, Object Detection, Depth Estimation, YOLO, Computer Vision, Internet of Things (IoT).

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