Blockchain-based Secure Supply Chain management using Identical Deep Multilingual Convolutional Neural Networks (IDMCNN)

The Warehouse Management System (WMS) is a section of software that allows the user to keep track of the inventory levels and the locations in real-time. Many logistics -based companies implement WMS for implementing Order Picking Systems (OPS). Typically, the WMS offers visibility of the enterprise 's activities by managing the supply chain for warehouse management. Typically, it uses work hands to take part in many tasks based on the output. It may lead to poor performance and an increase in implementation cost, resulting in unsatisfied customers. The existence of new markets makes the warehouses hold many orders in a short period. This leads to human errors as most humans are involved in this voice picking process. Also, there are some optimization -related issues due to the manual processes. For handling this situation, the order picking operation follows various aspects for solving a broad level of planning -based issues by guaranteeing good optimization strategies. This research implements an order picking system by combining blockchain and deep learning to improve associated issues and performance. A modified architecture using a deep neural network for recognizing human activity is explained. The architecture consists of Identical Deep Multilingual Convolutional Neural Networks (IDMCNN) for achieving better tracking performance by implementing the multiple inertial measurement units. The IDMCNN offers a better solution for handling optimization -related issues. Blockchain technology ensures security with data integrity and effectively communicates to the end-users.