An IoT-Enabled Secured Approach for Industrial Supply Chain Systems With Variational Autoencoders

The conventional industry has been recognized as one of the major causes of environmental pollution and waste due to its unsustainable supply chains. Traditional approaches failed to utilize real-time data effectively, which resulted in inefficiencies, weak security measures, and a lack of transparency in industrial supply chains. This paper proposes a closed-loop circular economy model that emphasizes material reuse, repair, and recycling by combining IoT-enabled supply chains with Variational Autoencoders (VAE). The advanced encryption standards (AES) are integrated with the VAE for secure data processing. In the proposed model, IoT devices collect real-time data about the materials and resources, and AES-enabled VAE provides secured and optimized decision-making. The performance of the proposed scheme is evaluated using various metrics, which include waste reduction, supply chain transparency, energy efficiency, environmental impact, and material flow efficiency. The model is compared with traditional linear supply chains, such as the take-make-dispose approach, and previous circular models, like cradle-to-cradle systems. The results show that the proposed model significantly improves green supply chain transparency, optimizes resources, and provides data security.