FlowPOS 2.0: A Technical Case Study of an AI-Assisted Point-of-Sale Prototype Using Computer Vision
Year: 2026
Type: preprint
Abstract: This technical case study presents FlowPOS 2.0, a collaborative AI-assisted point-of-sale prototype developed by NCAIR Group 4, Cohort 35. The system integrates computer vision, facial recognition and customer enrolment, YOLOv8-based product detection, and an automated checkout workflow. The manuscript discusses the system architecture, implementation approach, integration process, debugging, testing, reported model performance, limitations, and opportunities for further development. The author's individual contributions included work on the facial-recognition and customer-enrolment system, system integration, debugging, testing, technical documentation, and project presentation. The wider system was developed collaboratively by the project team. This work is presented as a technical case study and has not been independently peer-reviewed.
Author: Adewola, Oluwatobi
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225560843