An automated alarm system for food safety by using electronic invoices


Autoři: Wan-Tzu Chang aff001;  Yen-Po Yeh aff003;  Hong-Yi Wu aff002;  Yu-Fen Lin aff003;  Thai Son Dinh aff002;  Ie-bin Lian aff001
Působiště autorů: Data Science Research Center, National Changhua University of Education, Changhua, Taiwan aff001;  Institute of Statistics and Information Science, National Changhua University of Education, Changhua, Taiwan aff002;  Changhua County Public Health Bureau, Changhua, Taiwan aff003;  Innovation and Policy Center for Population Health and Sustainable Environment, College of Public Health, National Taiwan University, Taipei, Taiwan aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0228035

Souhrn

Background

Invoices had been used in food product traceability, however, none have addressed the automated alarm system for food safety by utilizing electronic invoice big data. In this paper, we present an alarm system for edible oil manufacture that can prevent a food safety crisis rather than trace problematic sources post-crisis.

Materials and methods

Using nearly 100 million labeled e-invoices from the 2013‒2014 of 595 edible oil manufacturers provided by Ministry of Finance, we applied text-mining, statistical and machine learning techniques to “train” the system for two functions: (1) to sieve edible oil-related e-invoices of manufacturers who may also produce other merchandise and (2) to identify suspicious edible oil manufacture based on irrational transactions from the e-invoices sieved.

Results

The system was able to (1) accurately sieve the correct invoices with sensitivity >95% and specificity >98% via text classification and (2) identify problematic manufacturers with 100% accuracy via Random Forest machine learning method, as well as with sensitivity >70% and specificity >99% through simple decision-tree method.

Conclusion

E-invoice has bright future on the application of food safety. It can not only be used for product traceability, but also prevention of adverse events by flag suspicious manufacturers. Compulsory usage of e-invoice for food producing can increase the accuracy of this alarm system.

Klíčová slova:

Decision trees – Machine learning – Neural networks – Oils – Safety – Support vector machines – Text mining – Food chains


Zdroje

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Článek vyšel v časopise

PLOS One


2020 Číslo 1