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General Information
    • ISSN: 2010-3751 (Print)
    • Frequency: Semi-annual
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Pascal Lorenz
    • Executive Editor: Ms. Tina Yuen
    • Abstracting/ Indexing: Crossref, Electronic Journals LibraryGoogle Scholar, EBSCO, etc.
    • E-mail:  editor@ijfcc.org
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Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the Editor-in-Chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2026 Vol.15(2): 49-55
DOI: 10.18178/ijfcc.2026.15.2.632

Implementation of IoT & AI Technology for Quality Enhancement in Real-time Pharmaceutical Storage Monitoring

Sally Musattat*, Taif Alsharif, and Salma Elhag*
Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia
Email: smusattat0001@stu.kau.edu.sa (S.M.); talsharif0058@stu.kau.edu.sa (T.A.); smomar@kau.edu.sa (S.E.)
*Corresponding author

Manuscript received April 8, 2026; revised May 11, 2026; accepted June 10, 2026, published July 17, 2026

Abstract—With the development of Artificial Intelligence (AI), scientists have been focusing on utilizing real-time pharmaceutical monitoring for multiple purposes. One of the main sectors benefiting from this is minimizing wastage. In this study, we introduce the ability to monitor pharmaceutical products through the integration of AI and the Internet of Things (IoT) to achieve real-time product management and waste reduction. The study introduces smart sensors that monitor the temperature and humidity of the medication in pharmacy cold storage. The system involves a decision mechanism to check for abnormalities. If regular conditions are recorded, the storage process is continued normally, and data are auto logged. However, if abnormalities are detected, the
AI-assisted controller executes a bounded automatic adjustment of cooling parameters while simultaneously notifying the supervisor; all events are recorded for audit. In addition, we model the As-Is/To-Be processes using Business Process Model Notation (BPMN) and evaluate a 30-day Bizagi simulation for pharmacy cold storage. KPIs indicate substantial gains such as faster detection, alerting, corrective response, and improved auto-logging coverage. These results support the feasibility of the AI and IoT approach for improving real-time pharmaceutical monitoring and reducing potential wastage.


Keywords—real-time monitoring, pharmaceutical, storage monitoring, Internet of Things (IoT), Artificial Intelligence (AI)

[PDF]

Cite: Sally Musattat, Taif Alsharif, and Salma Elhag, "Implementation of IoT & AI Technology for Quality Enhancement in Real-time Pharmaceutical Storage Monitoring," International Journal of Future Computer and Communication, vol. 15, no. 2, pp. 49-55, 2026.


Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0)
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