SmartQ-Bill: AI-Driven Voice Billing with Quantum

Author

Satishkumar Patnala, R. Venkata Rama Ganesh Sashank, M.Pallavi, S.Lakashmana Rao, S.Likhith, S.Bala Subramanyam Achary


Abstract

 Traditional billing systems in supermarkets, grocery stores and other retail environments often rely on manual product entry and conventional billing methods. This can lead to time-consuming processes and billing errors, especially in crowded and noisy environments. This paper presents SmartQ-Bill, an AI-driven voice-based billing system that enables cashiers to generate bills using voice commands. The system captures cashier speech through a directional microphone, applies noise reduction using the noisereduce library, and performs speaker authentication before processing commands. OpenAI Whisper converts speech into text, while a Retrieval-Augmented Generation (RAG) framework integrated with ChromaDB retrieves relevant product information, including product names and prices. An AI-based confirmation mechanism allows cashiers to verify recognized items and quantities before finalizing the bill. To introduce a quantum computing component, IBM Qiskit is used to generate a unique Quantum-Generated Bill Identifier (QGBI) for each invoice, supporting bill identification and traceability. The system uses ReportLab for digital invoice generation and PyPDF for PDF management, with a user-friendly web interface for accessing generated bills. The paper describes the system architecture, voice-processing workflow, RAG-based product retrieval, bill validation and quantum identifier generation. The proposed approach aims to reduce manual effort, improve billing accuracy, support secure invoice management and provide an efficient voice-based billing solution for modern retail environments.


Keywords

AI-Driven Voice Billing, Speaker Authentication, Noise Reduction, Quantum Computing, Quantum Random Number Generation (QRNG).



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