E-ISSN 3115-5057 | ISSN 3115-5049
 
2025, Vol: 2, Issue: 2
2 / 2Current Issue Online FirstArchiveAims and ScopeAbstracting & Indexing

Review Article
Online Published: 29 Jun 2025
 


IoT-based Beverage Fraud Detection: A Theoretical Review

Abraham Usman Usman, Stephen Seyi Oyewobi, Abdulkadir Olayinka Abdulbaki, Bala Alhaji Salihu, Thomas A Mamman, Johnson A Ajiboye.


Abstract
This theoretical review explores the foundational theories, frameworks, and models relevant to the design of an Artificial Intelligence (AI) and Internet of Things (IoT)-based system for detecting counterfeit and expired carbonated beverages in the Nigerian market. The growing incidence of beverage fraud, including dilution, mislabeling, and expiration concealment, necessitates the adoption of advanced detection mechanisms. This study explores the use of Bayesian Linear Regression (BLR) to analyze caffeine and CO₂ concentrations within established theories from food safety, sensor analytics, and machine learning. By comparing and critiquing traditional and modern approaches, the review highlights the strengths of integrated IoT and Machine Learning (ML) technologies for scalable, real-time quality monitoring. The key finding from the review is that integrating IoT-enabled sensors, BLR, and ML within the Fake Beverages Detection Systems (FaBEDs) framework offers a scalable, real-time, and interpretable approach for detecting counterfeit and expired carbonated beverages, particularly suitable for low-resource settings like Nigeria. This work contributes a critical perspective on how theoretical models can inform practical implementations for safeguarding public health and ensuring beverage supply chain integrity in developing economies

Key words: Bayesian Linear Regression, Beverage, Counterfeit, Fraud, Internet of Things, Machine Learning


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Abraham Usman Usman
Articles by Stephen Seyi Oyewobi
Articles by Abdulkadir Olayinka Abdulbaki
Articles by Bala Alhaji Salihu
Articles by Thomas A Mamman
Articles by Johnson A Ajiboye
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Usman AU, Oyewobi SS, Abdulbaki AO, Salihu BA, Mamman TA, Ajiboye JA. IoT-based Beverage Fraud Detection: A Theoretical Review. CUJOSTECH. 2025; 2(2): 117-124. doi:10.5455/CUJOSTECH.251012

Web Style

Usman AU, Oyewobi SS, Abdulbaki AO, Salihu BA, Mamman TA, Ajiboye JA. IoT-based Beverage Fraud Detection: A Theoretical Review. https://www.cujostech.com.ng/?mno=266497 [Access: June 27, 2026]. doi:10.5455/CUJOSTECH.251012

AMA (American Medical Association) Style

Usman AU, Oyewobi SS, Abdulbaki AO, Salihu BA, Mamman TA, Ajiboye JA. IoT-based Beverage Fraud Detection: A Theoretical Review. CUJOSTECH. 2025; 2(2): 117-124. doi:10.5455/CUJOSTECH.251012


Vancouver/ICMJE Style

Usman AU, Oyewobi SS, Abdulbaki AO, Salihu BA, Mamman TA, Ajiboye JA. IoT-based Beverage Fraud Detection: A Theoretical Review. CUJOSTECH. (2025), [cited June 27, 2026]; 2(2): 117-124. doi:10.5455/CUJOSTECH.251012


Harvard Style

Usman, A. U., Oyewobi, . S. S., Abdulbaki, . A. O., Salihu, . B. A., Mamman, . T. A. & Ajiboye, . J. A. (2025) IoT-based Beverage Fraud Detection: A Theoretical Review. CUJOSTECH, 2 (2), 117-124. doi:10.5455/CUJOSTECH.251012


Turabian Style

Usman, Abraham Usman, Stephen Seyi Oyewobi, Abdulkadir Olayinka Abdulbaki, Bala Alhaji Salihu, Thomas A Mamman, and Johnson A Ajiboye. 2025. IoT-based Beverage Fraud Detection: A Theoretical Review. Confluence University Journal of Science and Technology, 2 (2), 117-124. doi:10.5455/CUJOSTECH.251012


Chicago Style

Usman, Abraham Usman, Stephen Seyi Oyewobi, Abdulkadir Olayinka Abdulbaki, Bala Alhaji Salihu, Thomas A Mamman, and Johnson A Ajiboye. "IoT-based Beverage Fraud Detection: A Theoretical Review." Confluence University Journal of Science and Technology 2 (2025), 117-124. doi:10.5455/CUJOSTECH.251012


MLA (The Modern Language Association) Style

Usman, Abraham Usman, Stephen Seyi Oyewobi, Abdulkadir Olayinka Abdulbaki, Bala Alhaji Salihu, Thomas A Mamman, and Johnson A Ajiboye. "IoT-based Beverage Fraud Detection: A Theoretical Review." Confluence University Journal of Science and Technology 2.2 (2025), 117-124. Print. doi:10.5455/CUJOSTECH.251012


APA (American Psychological Association) Style

Usman, A. U., Oyewobi, . S. S., Abdulbaki, . A. O., Salihu, . B. A., Mamman, . T. A. & Ajiboye, . J. A. (2025) IoT-based Beverage Fraud Detection: A Theoretical Review. Confluence University Journal of Science and Technology, 2 (2), 117-124. doi:10.5455/CUJOSTECH.251012


Author LoginReviewer LoginEditorial PoliciesEditorial Review PolicyPeer Review PolicyEditorial & Peer Review ProcessAuthor's Rights and ObligationsConflict of Interest PolicyPlagiarism PolicyProtection of Research Participants (Statement On Human And Animal Rights)Statement of Informed ConsentCopyright Information

About Confluence University Journal of Science and Technology

Confluence University Journal of Science and Technology (CUJosTech) is the official Journal of the Confluence University of Science and Technology (C ... Read more.



For best results, please use Internet Explorer or Google Chrome.

Contact Information

Dr Daniel O. Apeh
Journal Secretary
Room 21, Block C, Faculty of Science Building
cujostech@custech.edu.ng
+234(0)7033395643