International Journal of Technology and Applied Science

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Volume 17 Issue 11
November 2026

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SCANOVA: Intelligent Cashier-Less Retail Billing System

Author(s) Mr. Darshan G, Prof. Dr. Abhilash C N, Mr. Tarun B G, Mr. H J Suhas, Mr. Vinesh Mullai G
Country India
Abstract This research presents SCANOVA, an intelligent cashier-less retail billing system designed to simplify retail checkout and improve transaction security. The system integrates barcode-based product identification, digital cart management, automated billing with 18% GST calculation, UPI payments, and digital invoice generation into a single web application. It uses Vite and TypeScript for the frontend and Supabase for authentication, PostgreSQL database storage, and Row Level Security. Barcode tampering detection is performed before a product is added to the cart, while machine learning-based anomaly analysis evaluates transaction risk. The prototype includes 40 products across 14 brands and was tested using normal checkout, an unusual shopping basket, and a tampered barcode. The observed results demonstrate the integration of the main modules and the intended handling of different checkout conditions. However, further evaluation using labelled transaction data and standard performance metrics is required to establish the overall accuracy of fraud detection.
Keywords Cashier-Less Retail, Barcode Scanning, Barcode Tampering Detection, Fraud Detection, Anomaly Detection, Isolation Forest, Machine Learning, UPI Payment, Digital Billing, Smart Retail
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 17, Issue 11, November 2026
Published On 2026-11-10
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Crossref DOI prefix of IJTAS is 10.71097/IJTAS

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