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An Innovative and Smart Agriculture Platform for Improving the Coffee Value Chain and Supply Chain

Lookup NU author(s): Dr Duy NguyenORCiD

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Abstract

Vietnam is the world’s second biggest producer of coffee and has been an exporter for several decades. However, Vietnam has been facing many well-documented issues and challenges in the whole coffee supply chain such as climate change; low productivity, poor quality and high cost; excessive use of fertilizing products and irrigations; poor collection, processing and storage solution; low sustainability and limited value-added coffee products; and low applications of smart and sustainable agriculture solutions. This paper introduces an innovative and smart agriculture (INNSA) platform for the creation and operation of a sustainable coffee value chain, with the focus on enhanced quality and added values for key elements of the coffee supply chain in Vietnam. The platform is designed based on the foundations of the key enabling digital transformation and smart agriculture technologies: Smart devices and Internet of Things, big data, artificial intelligence, blockchain and source traceability technologies, and sustainable design and manufacturing. The INNSA platform has the following key features: a smart database with real-time data inputs and updates, cost-effectiveness, and open-architectures for effective integrations of the enabling digital transformation and smart agriculture technologies. The smart platform and ecosystem of INNSA provides the information portal and open-access database for all key factors of coffee supply chain, enabling them to join and interact with each other to bring the coffee industry of Vietnam to a higher level, well-recognized in terms of values, branding and sustainability.


Publication metadata

Author(s): Nguyen VD, Pham TC, Le CH, Huynh TT, Le TH, Packianather M

Editor(s): Thi Dieu Linh Nguyen, Joan Lu

Series Editor(s): Janusz Kacprzyk

Publication type: Book Chapter

Publication status: Published

Book Title: Machine Learning and Mechanics Based Soft Computing Applications

Year: 2023

Pages: 185-197

Print publication date: 28/02/2023

Online publication date: 28/02/2023

Acceptance date: 28/02/2023

Series Title: Studies in Computational Intelligence book series (SCI,volume 1068)

Publisher: Springer

Place Published: Singapore

URL: https://doi.org/10.1007/978-981-19-6450-3_19

DOI: 10.1007/978-981-19-6450-3_19

Library holdings: Search Newcastle University Library for this item

ISBN: 9789811964497


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