Citation :

Chona R. Dagatan, Jestoni P. Tan, Joy Stiffany A. Amodia, Lei Jo C. Bacu, Brett H. Callanga, Jeff Niño G. Caparoso, Avril Mae O. Malaga, Jedelou B. Pepito, "Development of a Smart Wearable Assistive Device with Object Detection and Text-to-Speech Functionality for Visually Impaired Individuals using Raspberry Pi," International Journal of Engineering Trends and Technology (IJETT), vol. 74, no. 8, pp. 99-108, 2026. Crossref, https://doi.org/10.14445/22315381/IJETT-V74I8P107

Abstract

Visually impaired individuals struggle in terms of their mobility, awareness, and overall quality of life. Traditional aids, such as canes, offer only limited assistance. This capstone project aims to develop a smart wearable device to enhance environmental awareness and assistance for visually impaired individuals in Danao City. The smart wearable assistive device is composed of a Raspberry Pi 4, ultrasonic sensors, a web camera, and text-to-speech technology that is used to deliver audio feedback that helps in better comprehension of information for these individuals. Experimental tests were conducted using percent error and paired t-tests to evaluate the overall performance of the wearable device. Survey questionnaires and interviews were also conducted to test the effectiveness of the device based on participants’ experiences. The quantitative results show that the smart wearable device consistently underperformed in its different functions. In distance range detection, the system has an average distance of 2.5 meters from the desired range, with a statistical analysis (t = 6.74, p < 0.05) indicating a significant difference. Object detection accuracy identifies an average of 9 out of 15 objects with a statistical analysis of (t = -8.96, p < 0.001) and has an effect size of 2.31. The system shows an average of 1-2 missed words per trial and a statistical analysis of (t = -5.13, p < 0.001). Overall, the findings of this study confirm that the smart wearable device's potential, specifically in text-to-speech systems, helps to enhance independence and confidence in common environments.

Keywords

Computer vision, Object detection, Text-to Speech, YOLO, Wearable device.

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