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In the rapidly growing consumer electronics industry, continuous innovation drives increasing demand for smart devices and advanced gadgets. However, this sector faces changing demands and complex supply chains due to the management of rapid technological advancements and consumer expectations. Seamless communication between suppliers and consumers is essential to optimize production processes, minimize waste, and enhance overall customer satisfaction. In response to these demands, this paper presents a solution that combines Digital Twins (DT) and blockchain to improve security and efficiency in metaverse-inspired consumer-oriented supply chains. Herein, DT is used to represent products in virtual spaces and blockchain secures sensitive information using encryption and access controls. Our objective is to create a transparent, secure, and user-friendly system where consumers and suppliers can interact in real-time to verify product details and access important information of featured tasks like warranties and payment settlement. Smart contracts automates these tasks to make processes faster and more reliable. Through experiments, we tested how well the system maintains product integrity, authenticates transactions, and supports consumer-oriented supply chain (CSC) operations. Comparative analysis shows that our approach improves security, performance, and scalability over existing methods. Furthermore, the proposed system not only enhances security, trust, and transparency in CSC but also sets a higher standard for consumer demands and satisfaction. The findings point to the potential solution for future innovations in metaverse-driven CSC management systems. 

In the era of pervasive digital connectivity, intelligent surveillance systems (ISS) have become essential tools for ensuring public safety, protecting critical infrastructure, and deterring security threats in various environments. The current state of these systems heavily relies on the computational capabilities of mobile devices for tasks such as real-time video analysis, object detection, and tracking. However, the limited processing power and energy constraints of these devices hinder their ability to perform these tasks efficiently and effectively. The dynamic nature of the surveillance environment also adds complexity to the task-offloading process. To address this issue, mobile edge computing (MEC) comes into play by offering edge servers with higher computational capabilities and proximity to mobile devices. It enables ISS by offloading computationally intensive tasks from resource-constrained mobile devices to nearby MEC servers. Therefore, in this paper, we propose and implement an energy-efficient and cost-effective task-offloading framework in the MEC environment. The amalgamation of binary and partial task-offloading strategies is used to achieve a cost-effective and energy-efficient system. We also compare the proposed framework in MEC with mobile cloud computing (MCC) environments. The proposed framework addresses the challenge of achieving energy-efficient and cost-effective solutions in the context of MEC for ISS. The iFogSim simulator is used for implementation and simulation purposes. The simulation results show that the proposed framework reduces latency, cost, execution time, network usage, and energy consumption.