TY - GEN
T1 - Design of an AI-Powered Smart Shopping Cart with Inclusive Accessibility Features
AU - Calderón, Lucía Gabriela Sarmiento
AU - Galván, José Guillermo Balbuena
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper presents the design and development of an AI-Powered Smart Shopping Cart with inclusive accessibility features tailored for supermarkets in Peru. Supermarkets face challenges to improve accessibility, reduce wait times, and provide personalized customer experiences, particularly for people with disabilities. In Peru, these issues are exacerbated by infrastructural limitations and a lack of technological solutions in retail. To address this, we introduce a system that includes an AI virtual assistant utilizing prompting for natural and personalized user interactions, AI-driven product recognition via cameras, and a height-adjustable mechanism designed specifically for wheelchair users. The product recognition system uses YOLOv8obb for barcode detection and a custom convolutional neural network architecture for barcode reading. This system not only improves accessibility, but also achieves a precision rate of 97.8% in real world environments, surpassing existing solutions. This design represents a significant advancement in the integration of technology and accessibility in retail environments, offering substantial benefits for both consumers and supermarkets.
AB - This paper presents the design and development of an AI-Powered Smart Shopping Cart with inclusive accessibility features tailored for supermarkets in Peru. Supermarkets face challenges to improve accessibility, reduce wait times, and provide personalized customer experiences, particularly for people with disabilities. In Peru, these issues are exacerbated by infrastructural limitations and a lack of technological solutions in retail. To address this, we introduce a system that includes an AI virtual assistant utilizing prompting for natural and personalized user interactions, AI-driven product recognition via cameras, and a height-adjustable mechanism designed specifically for wheelchair users. The product recognition system uses YOLOv8obb for barcode detection and a custom convolutional neural network architecture for barcode reading. This system not only improves accessibility, but also achieves a precision rate of 97.8% in real world environments, surpassing existing solutions. This design represents a significant advancement in the integration of technology and accessibility in retail environments, offering substantial benefits for both consumers and supermarkets.
KW - CNN
KW - Smart shopping cart
KW - YoloOBB
KW - barcode recognition
KW - neural networks
UR - https://www.scopus.com/pages/publications/105006588428
U2 - 10.1109/ICCE63647.2025.10930203
DO - 10.1109/ICCE63647.2025.10930203
M3 - Conference contribution
AN - SCOPUS:105006588428
T3 - Digest of Technical Papers - IEEE International Conference on Consumer Electronics
BT - 2025 IEEE International Conference on Consumer Electronics, ICCE 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE International Conference on Consumer Electronics, ICCE 2025
Y2 - 11 January 2025 through 14 January 2025
ER -