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ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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QR Based Online Payment System For Enhanced Convivence Using ML

Authors: Prof. Rahul D. Ingle; Prof. Rohan B. Kokate; Jyoti Ramesh Lanjewar;

QR Based Online Payment System For Enhanced Convivence Using ML

Abstract

The rapid advancement of digital technology has significantly transformed financial transactions, leading to the widespread adoption of cashless payment systems. Among these, QR code-based payment systems have emerged as one of the most convenient and efficient methods for conducting fast and contactless transactions. However, despite their growing popularity, these systems still face critical challenges such as transaction fraud, unauthorized access, phishing attacks, and security vulnerabilities. To overcome these limitations, there is a need to integrate intelligent technologies that can enhance both security and user experience. This project presents the design and development of a QR Based Online Payment System for Enhanced Convenience Using Machine Learning (ML). The primary objective of the system is to provide a secure, fast, and user-friendly digital payment platform that allows users to make payments simply by scanning QR codes. The system eliminates the need for physical cash, card swiping, or manual bank details entry, thereby reducing transaction complexity and improving efficiency. A key feature of the proposed system is the integration of Machine Learning-based fraud detection mechanisms. The ML model continuously analyzes transaction patterns, user behavior, device information, and payment history to identify unusual or suspicious activities. By using classification and anomaly detection techniques, the system can detect potential fraud in real time and prevent unauthorized transactions before they are completed. This enhances the overall trust and reliability of the payment platform. The system also includes essential modules such as secure user authentication, dynamic QR code generation, transaction processing, payment history tracking, and notification services. Each transaction is securely encrypted and stored in a centralized database to ensure data integrity and confidentiality. The platform is designed using modern web technologies to ensure scalability, responsiveness, and compatibility across multiple devices. From a functional perspective, the system supports both users and merchants, enabling seamless peer-to-merchant and peer to peer payments. Merchants can generate unique QR codes linked to their accounts, while users can scan and complete payments instantly. The inclusion of real-time alerts and dashboards helps users track their financial activities efficiently.

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green