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Article

Real-Time Electrical Energy Optimization in E-Commerce Systems Based on IoT and Mobile Agents

1
Innov’COM Laboratory, National Engineering School of Carthage, University of Carthage, Charguia II, Carthage 2035, Tunisia
2
School of Business and Creative Industries, University of the Sunshine Coast, Sippy Downs, QLD 4556, Australia
*
Author to whom correspondence should be addressed.
Information 2025, 16(7), 551; https://doi.org/10.3390/info16070551 (registering DOI)
Submission received: 4 April 2025 / Revised: 12 June 2025 / Accepted: 23 June 2025 / Published: 27 June 2025
(This article belongs to the Section Internet of Things (IoT))

Abstract

The integration of the Internet of Things (IoT) into mobile agent technology has fundamentally transformed the landscape of e-commerce by enabling intelligent, adaptive, and energy-efficient solutions. In this paper, we present a new system for integrating the information-sharing capability of IoT-enabled devices with the advanced abilities of mobile agents for the optimal utilization of energy when conducting e-commerce activity. The mobile agents are used as a mediating agent in the transaction and will capture operation data to share with stakeholders (not in the transaction) who might be able to provide services in association with that transaction. The operational data is collected, stored, and analyzed in real-time via IoT devices, facilitating adaptive decision-making while providing continuous monitoring of the system and servicing to improve energy management, efficiency, and operational performance. The combined IoT and energy capacity will enhance data sharing and provide more energy-efficient activities. The evaluation of the system was completed through simulations, as well as through real-world scenarios, achieving a decrease of approximately 27.8% in total energy consumption and savings of over 30% on operational costs. Moreover, the proposed architecture achieved a reduction of up to 38.9% for response times for resource management, under load, while also demonstrating a 50% reduction in response time for real-time event handling. Therefore, the effects of the proposed approach have been proven to be effective through simulations and real-world case studies, showing improvements in energy consumption and costs, as well as flexibility and adaptability. The findings of this study show that this framework not only minimizes energy consumption but also maximizes scalability, responsiveness to user demands, and robustness against variability in an e-commerce workload. This effort illustrates the potential for extending the lifetimes of e-commerce infrastructures and developing sustainable e-commerce models, demonstrating how IoT-based architectures can facilitate better resource allocation while achieving sustainability goals.
Keywords: Internet of Things (IoT); mobile agents; e-commerce; energy optimization; JADE; real-time monitoring; machine learning Internet of Things (IoT); mobile agents; e-commerce; energy optimization; JADE; real-time monitoring; machine learning

Share and Cite

MDPI and ACS Style

Shili, M.; Anwar, S. Real-Time Electrical Energy Optimization in E-Commerce Systems Based on IoT and Mobile Agents. Information 2025, 16, 551. https://doi.org/10.3390/info16070551

AMA Style

Shili M, Anwar S. Real-Time Electrical Energy Optimization in E-Commerce Systems Based on IoT and Mobile Agents. Information. 2025; 16(7):551. https://doi.org/10.3390/info16070551

Chicago/Turabian Style

Shili, Mohamed, and Sajid Anwar. 2025. "Real-Time Electrical Energy Optimization in E-Commerce Systems Based on IoT and Mobile Agents" Information 16, no. 7: 551. https://doi.org/10.3390/info16070551

APA Style

Shili, M., & Anwar, S. (2025). Real-Time Electrical Energy Optimization in E-Commerce Systems Based on IoT and Mobile Agents. Information, 16(7), 551. https://doi.org/10.3390/info16070551

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