Audio-Based Assistive Device for Boxed Product Detection for The Visually Impaired - Yoni, Muhammad Dzaky; Yendri, Dodon (Universitas Andalas, 2025)
Visually impaired individuals face challenges in recognizing and distinguishing boxed products, which are typically identified visually. This study aims to develop an audiobased assistive system for detecting boxed product packaging to enhance the independence of visually impaired individuals. The system utilizes the Single Shot Multibox Detector (SSD) MobileNetV2 algorithm for object detection and classification, with the Raspberry Pi 4 Model B as the main microcontroller and the Raspberry Pi Camera OV5647 for image capture. The HC-SR04 ultrasonic sensor is used to measure the distance of objects from the user, while the output information is provided through wireless earphones in the form of audio. Experimental results show that the system can detect and classify boxed products with an accuracy of 95%, precision of 96.8%, recall of 98%, and an F1-Score of 97.4%. This system provides real-time audio feedback, assisting visually impaired individuals in identifying products without the need for tactile exploration.