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利用区块链和物联网提升优质可可豆发酵过程中的数据安全性

Improving Data Security with Blockchain and Internet of Things in the Gourmet Cocoa Bean Fermentation Process.

作者信息

Abijaude Jauberth, Sobreira Péricles, Santiago Levy, Greve Fabíola

机构信息

Computer Science Institute, Federal University of Bahia, Salvador 40170-110, Bahia, Brazil.

Exact Science Departament, Santa Cruz State University, Ilheus 45662-900, Bahia, Brazil.

出版信息

Sensors (Basel). 2022 Apr 15;22(8):3029. doi: 10.3390/s22083029.

DOI:10.3390/s22083029
PMID:35459017
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9031426/
Abstract

Brazil was one of the largest cocoa producers in the world, mainly supported by the South of Bahia region. After the 1980s, the witch-broom disease demolished plantations, and farmers were forced into bankruptcy. The worldwide search for gourmet cocoa has rekindled interest in this production, whose fermentation process is a key step in obtaining fine cocoa, thanks to the fact that many processing properties and sensory attributes are developed in this phase. This article presents a blockchain-IoT-based system for the control and monitoring of these events, aiming to catalog in smart contracts valuable information for improvement of the cocoa fermentation process, and future research. Blockchain is used as a distributed database that implements an application-level security layer. A proof of concept was modeled and the performance of the emulated system was evaluated in the OMNet simulator, where a technique based on the SNMP protocol was applied to reduce the amount of data exchanged and resources served/consumed in this representation. Then, a physical platform was developed and preliminary experiments were performed on a real farm, as a way to verify the improvement of the cocoa fermentation process when using a technological approach.

摘要

巴西曾是世界上最大的可可生产国之一,主要产区在巴伊亚州南部。20世纪80年代后,女巫扫帚病摧毁了种植园,农民被迫破产。全球对优质可可的追求重新点燃了人们对这种产品的兴趣,其发酵过程是获得优质可可的关键步骤,因为许多加工特性和感官属性都在这个阶段形成。本文提出了一种基于区块链物联网的系统,用于控制和监测这些事件,旨在将有价值的信息编入智能合约,以改进可可发酵过程并用于未来研究。区块链用作实现应用层安全层的分布式数据库。构建了一个概念验证模型,并在OMNet模拟器中评估了仿真系统的性能,在该模拟器中应用了一种基于SNMP协议的技术,以减少在此表示中交换的数据量和所服务/消耗的资源。然后,开发了一个物理平台,并在一个真实农场进行了初步实验,以此验证采用技术方法时可可发酵过程的改进情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/e1a650021cdb/sensors-22-03029-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/c386057c37c3/sensors-22-03029-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/71b49b769af3/sensors-22-03029-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/18c655278beb/sensors-22-03029-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/f073d66a54da/sensors-22-03029-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/b2b6d3c3941a/sensors-22-03029-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/f85499f03c12/sensors-22-03029-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/10d8038a875e/sensors-22-03029-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/7cdad8736647/sensors-22-03029-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/e903deb2d225/sensors-22-03029-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/e1a650021cdb/sensors-22-03029-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/c386057c37c3/sensors-22-03029-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/71b49b769af3/sensors-22-03029-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/18c655278beb/sensors-22-03029-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/f073d66a54da/sensors-22-03029-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/b2b6d3c3941a/sensors-22-03029-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/f85499f03c12/sensors-22-03029-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/10d8038a875e/sensors-22-03029-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/7cdad8736647/sensors-22-03029-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/e903deb2d225/sensors-22-03029-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932c/9031426/e1a650021cdb/sensors-22-03029-g010.jpg

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本文引用的文献

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Prediction of fermentation index of cocoa beans (Theobroma cacao L.) based on color measurement and artificial neural networks.
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