The Utilization of Machine Learning and Blockchain in the Safe Handling of a Supply Chain in IoT Ecosystems

Abstract

The revolution in the management of supply chain through introduction of the Internet of Things (IOT) devices will be pushed by automation since the devices can be tracked and monitored in real time. Storing much information that is highly secured however is a very hectic process. The databases that were established with the old systems of the supply chain are of a centralized variety and can be easily tampered with, hence, susceptible to in-efficient processes besides being vulnerable to security risk. The given paper is devoted to the domain of the supply chain security, transparency, and efficiency in regard to the opportunities of the Blockchain and Machine Learning (ML). Blockchain has also been termed as irreconcilable decent and distributed ledger that creates certain transactions that bode well in respect to the other end of the scale is data quality and ML that provides an idea on the supply chain, tracking anomaly in addition to intelligent decision-making. The two technologies are capable of coming up with an empowering technology that will further increase the level of trust the company will enjoy, reduce the importance of the money used in the course of operation and the outcome of it will be the real time decision making. The hypothesis of the paper posits the descriptions of the application, the perceived gains and the challenges and how they are going to be incorporated in the current supply chains of the technologies. The work integrates the possibilities of the Machine Learning and the Blockchain phenomenon and explains the conceptual model, and after that, the synergetic dilation can be an adequate, efficient, and extensive solution to the problem of supply chain management in the contemporary world.