Spatial-Temporal Event Analysis as a Prospective Approach for Signalling Emerging Food Fraud-Related Anomalies in Supply Chains

One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food pa...

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Bibliographic Details
Published in:Foods 2022-12, Vol.12 (1), p.61
Main Authors: Jiménez-Carvelo, Ana M, Li, Pengfei, Erasmus, Sara W, Wang, Hui, van Ruth, Saskia M
Format: Article
Language:English
Subjects:
Alliances
Anomalies
Artificial intelligence
Codes
Collaboration
Communication
Consumers
Counterfeiting
Food chains
food crime
food fraud
Food packaging
Food products
Food quality
Food safety
Food science
Food supply
Fraud
Information systems
Internet of Things
Management
smart tags
Spatial analysis
spatial-temporal data
supply chain
Supply chains
traceability
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Summary:One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.
ISSN:2304-8158
2304-8158
DOI:10.3390/foods12010061