Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)

Research on Meat Product Traceability System Based on Two Dimensional Code

Authors
Yanbai Wang, Lu Tan
Corresponding Author
Yanbai Wang
Available Online November 2016.
DOI
10.2991/aiie-16.2016.87How to use a DOI?
Keywords
two dimensional code; origin; meat product
Abstract

Meat products safety related to the national economy and the people's livelihood, the relationship between the national health. Meat products in the breeding, slaughter, storage and sales process of real-time monitoring and the establishment of meat products safety traceability system is the main means to improve the status of meat products. Objective to improve the safety of meat products, meat products through the establishment of two-dimensional code technology based on traceability management system, so that consumers understand the meat products in the breeding, slaughtering, storage and sales process of the right to know, to increase the transparency of information of meat products in the whole process flow of.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-271-8
ISSN
1951-6851
DOI
10.2991/aiie-16.2016.87How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yanbai Wang
AU  - Lu Tan
PY  - 2016/11
DA  - 2016/11
TI  - Research on Meat Product Traceability System Based on Two Dimensional Code
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 382
EP  - 384
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.87
DO  - 10.2991/aiie-16.2016.87
ID  - Wang2016/11
ER  -