Distributed Ledger Technology for Transparent and Secure Warehouse Inventory Tracking

The rapid growth of global trade and e-commerce has placed unprecedented demands on warehouse management systems (WMS), emphasizing the need for accuracy, efficiency, and security in inventory tracking. Traditional systems often fall short, facing challenges such as data inconsistencies, lack of transparency, and vulnerability to fraud or cyberattacks. To address these issues, this research explores the integration of Distributed Ledger Technology (DLT), commonly known as Blockchain, and Artificial Intelligence/Machine Learning (AI/ML) within WMS from a software engineering perspective. Blockchain, with its decentralized, immutable, and transparent ledger capabilities, ensures robust security and accountability in warehouse operations. By eliminating intermediaries and providing a tamper-proof record of transactions, Blockchain enhances the traceability of inventory data, thereby reducing errors and fraud. AI/ML, on the other hand, empowers WMS through predictive analytics, demand forecasting, and anomaly detection, enabling proactive decision-making and optimizing resource allocation. Together, these technologies form a cohesive framework that not only addresses operational inefficiencies but also strengthens supply chain integrity.

This article examines the synergistic role of Blockchain and AI/ML in transforming warehouse management practices. It highlights their applications in secure inventory tracking, automated verification of goods, and real-time monitoring of supply chain activities. Furthermore, it presents a scalable model for integrating these technologies into existing WMS, emphasizing enhanced transparency, security, and efficiency. The findings underscore the potential of these advancements to revolutionize supply chain and logistics operations, paving the way for a new era of secure and intelligent warehouse management systems.