Analyzing Smart Inventory Management System Performance Over Time with State-Based Markov Model and Reliability Approach, Enhanced by Blockchain Security and Transparency

DOI: https://doi.org/10.19139/soic-2310-5070-2127
Keywords: Smart Supply Chain Management, Internet of Things, Blockchain, Arduino

Abstract

In response to the evolving demands of modern inventory management, this paper introduces a quantitative mathematical model aimed at assessing the performance of a smart inventory management system, emphasizing the integration of blockchain technology to enhance security and transparency. By considering essential hardware components, including ESP32 module, HC-SR04 ultrasonic sensor, battery, and jumper wires, the model utilizes Markov modeling and a reliability-based approach. Its primary objective is to enable timely repair and maintenance activities, ensuring sustained system availability by identifying and addressing weak components. Efficient operation of all system parts is critical for the timely transmission of inventory data. Through the incorporation of blockchain technology, the study addresses security and transparency concerns, alongside evaluating key reliability metrics such as reliability, unreliability, and Mean Time to Failure (MTTF). Sensitivity analysis identifies critical components, highlighting the importance of maintenance for components like the switch and servo motor. The research underscores the role of blockchain technology in fortifying security and transparency in smart inventory management systems, alongside emphasizing the significance of reliability metrics in system performance optimization.

Author Biographies

NABIL CHBAIK, 2IACS Laboratory, ENSET, Hassan II University of Casablanca, Mohammedia, Morocco
Nabil Chbaik Received the degree in engineering from Mohammed VI International Academy of Civil Aviation Casablanca, with versatile training in industrial and production engineering. He is currently pursuing the Ph.D. degree with the Computer Science, Artificial Intelligence, and Cyber Security Laboratory (L2IACS), Hassan II University of Casablanca. He is a trainer Engineer at Mohammed VI Polytechnic University. His research interests in equipment supervision in smart supply chain environment using Internet of Things and Blockchain.
Azeddine KHIAT, 2IACS Laboratory, ENSET, Hassan II University of Casablanca, Mohammedia, Morocco
Azeddine Khiat Professor Researcher in the Department Mathematics and Computer Science, H.D.R. and Ph.D. in computer science, networks and telecommunications at ENSET Mohammedia, University Hassan II of Casablanca, Morocco. A researcher member on the Computing, Artificial Intelligence and Cyber Security laboratory (2IACS), Artificial Intelligence, Cybersecurity and Digital Trust team (IACSCN) at ENSET Mohammedia, University Hassan II of Casablanca, Morocco. Outstanding Reviewer on various indexed journals. organizing committee and Technical Program Committee of tens of international conferences. Published tens of refereed journal and conference papers. Her research interests are: Wireless Networks, QoS on mobile networks, Handover on wireless networks, networks, and telecommunications, SDN, new generation networks, security, cybersecurity, mobile learning, IoT, smart city, smart Grid, and industry 4.0. certified on several products and solutions among them: Fortinet NSE4, Microsoft Azure Administrator Associate, Juniper Associate, Juniper Cloud Associate, Huawei RS Associate, Oracle Associate and Red Hat Associate.
Ayoub BAHNASSE, ENSAM, Hassan II University of Casablanca, Casablanca, Morocco
Ayoub Bahnasse Received the Ph.D. degree in networks and telecommunication from Chouaib Doukkali University, Morocco. He is currently a Professor and a Researcher with ENSAM Casablanca, Hassan II University of Casablanca, Morocco, where he is also a Research Associate with the Information Treatment Laboratory, Faculty of Sciences Ben M’sik. He is a member of the ‘‘Big Data and Internet of Things Project for Urban Service’’ Project, Hassan II University of Casablanca. He has published tens of refereed journal and conference papers. His research interests include new-generation networks, security, mobile learning, wireless networks, quality of service, multimedia systems, the IoT, smart city, and MPLS. He is an organizing committee member and a technical program committee member of tens of international conferences in around 20 countries. He is an Outstanding Reviewer of various indexed journals, such as Computer Networks (Elsevier), Computers and Electrical Engineering (Elsevier), Computers and Security (Elsevier), IEEE TRANSACTIONS ON COMMUNICATIONS, Telecommunication Systems (Springer), Wireless Personal Communications (Springer), Mobile Networks and Applications (Springer), and tens of indexed journals. He has been certified in several products and solutions, among them are Fortinet NSE4, Microsoft Azure Administrator Associate, Juniper DevOps Associate, Juniper Cloud Associate, Juniper Design Associate, and Huawei RS Associate.
Hassan OUAJJI, ENSAM, Hassan II University of Casablanca, Casablanca, Morocco
Hassan Ouajji Received the degree (higher education) from the Department of Electronic and Electrical Engineering, ENSET Mohammedia. He is currently a Full Professor with the Department of Electronic and Electrical Engineering, ENSET Mohammedia. He is also a Research Member with the SSDIA Laboratory and the Head of the Network and Telecommunications Team, Hassan II University of Casablanca, Morocco. He has published tens of refereed journal and conference papers. He is a member of several scientific projects with Hassan II University of Casablanca. His research interests include acoustic electrical engineering, signal processing, electronic, networks, and telecommunications. He is an organizing committee member and a technical program committee member of tens of international conferences. He is an outstanding reviewer of various indexed journals.
Published
2024-10-06
How to Cite
CHBAIK, N., KHIAT, A., BAHNASSE, A., & OUAJJI, H. (2024). Analyzing Smart Inventory Management System Performance Over Time with State-Based Markov Model and Reliability Approach, Enhanced by Blockchain Security and Transparency. Statistics, Optimization & Information Computing, 13(2), 508-530. https://doi.org/10.19139/soic-2310-5070-2127
Issue
Vol 13 No 2 (2025)
Section
Research Articles
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