Artificial Intelligence Integration Method for Agricultural Product Supply Chain Quality Data Based on Block Chain

Author(s):  
Kun Wang
2021 ◽  
Vol 57 (9) ◽  
pp. 6244-6250
Author(s):  
LAKSHIT JAIN, KIRAN KARANDE

Product counterfeiting is a major issue in today’s world. These days product counterfeiting leads to around 1.05 lac crore rupees in India per year. As per a report by business standard, if even 50% of product counterfeiting is stopped with authentication, monitored properly and governed, it can save 50,000 crore rupees per year in India itself, then think about whole world. This research paper is based on the use of block chain along with artificial intelligence to curb the problem of product counterfeiting and maintain the transparency. This research paper also demonstrates the use of blockchain using R studio as a platform. R is a programming language mostly for data analytics purposes. So, the implementation of blockchain in R can give a wide exposure to the data to be analyzed and suitable insights and forecasts can also be made. The research findings give a holistic picture of all the variables that affect the supply chain of E-commerce industry. This study helps the supplier side in curbing their loses and also the consumer side in receiving the genuine product that build trust among both the stakeholders


2020 ◽  
Vol 5 (12) ◽  
pp. 19-23
Author(s):  
Hieu Bui Trong ◽  
Uyen Bui Thi Kim

It is wide known that the world has been moving towards a digital future over the years, and Industry 4.0 technologies are considered to be the way of the future. One of the most prominent of these technologies (including Block Chain, Internet of Things, Cloud Computing, Big Data, etc.) is Artificial Intelligence (AI), was introduced to develop and create “thinking machines” that are capable of mimicking, learning, and replacing human intelligence. However, its widespread acceptance as a decision-aid tool, AI has seen limited application in supply chain management (SCM). The purpose of this work is to identify the contributions of AI to SCM through a brief review of the existing literature. Besides, this paper reviews the past record of success in AI applications to SCM and identifies the most subfields of SCM in which to apply AI.


2021 ◽  
Vol 96 ◽  
pp. 135-146
Author(s):  
Rameshwar Dubey ◽  
David J. Bryde ◽  
Constantin Blome ◽  
David Roubaud ◽  
Mihalis Giannakis

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