Smart Shopping Carts: Reducing Checkout Queues with RFID and AWS Facial Recognition
This study evaluates the efficiency of an experimental checkout system compared to traditional supermarket checkout processes through trials conducted during low and high activity periods. The experimental system demonstrated significant efficiency improvements, reducing checkout times by approximately 73% during low activity and 84% during high activity. Survey data revealed that younger users (18–30 years) rated the UI (User Interface) friendliness highest at 8.70 and showed a 100% preference for the new system, experiencing fewer facial recognition issues and finding product offers largely relevant. Conversely, older users (51–70 years) preferred traditional systems, faced more facial recognition challenges, and rated the UI friendliness lower. These findings suggest the new system is effective and well-received by younger users but requires enhancements to better accommodate older users, underscoring its potential to improve the overall shopping experience while highlighting areas for broader acceptance.
Authors
- Victor M. Parasi Falcon
- Rodrigo Toconas Ocaña
- Sergio Andres Mego Peñaranda
Institutions
- Peruvian University of Applied Sciences (PE)
Publication Details
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1109/intercon63140.2024.10833475
- Citations
- 2
- Primary Topic
- IoT and GPS-based Vehicle Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.43