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Food Safety Network for Detecting Adulteration in Unsealed Food Products Using Topological Ordering

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Intelligent Information and Database Systems (ACIIDS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12034))

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Abstract

The food supply chains are vast and involve a lot of persons. It is highly probable that any person within the food supply chain can add adulterant in the food product to gain more profit. Therefore, providing safe food through the chain is a big challenge. Though sealed food products can be tracked using various existing technologies such as using IoT devices or by chemical analysis, the traceability of unsealed food products is an unexplored domain. To address this problem, this paper proposes an adulterant check algorithm based on topological ordering. The proposed algorithm checks the adulterant nodes in the unsealed food product supply chain. Additionally, we also monitor the transactions in the unsealed food product supply chain and store the provenance information in the graph database. Thus, we provide a low cost, traceable, adulteration-free unsealed food supply chain.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, India

    Arpan Barman, Amrita Namtirtha & Animesh Dutta

  2. Documentation Research and Training Centre, Indian Statistical Institute, Bangalore, Bangalore, India

    Biswanath Dutta

Authors
  1. Arpan Barman
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  2. Amrita Namtirtha
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  3. Animesh Dutta
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  4. Biswanath Dutta
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Corresponding author

Correspondence to Arpan Barman .

Editor information

Editors and Affiliations

  1. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

    Kietikul Jearanaitanakij

  3. Faculty of Computer Science and Information, University Teknologi Malaysia, Kuala Lumpur, Malaysia

    Ali Selamat

  4. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

    Suphamit Chittayasothorn

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Barman, A., Namtirtha, A., Dutta, A., Dutta, B. (2020). Food Safety Network for Detecting Adulteration in Unsealed Food Products Using Topological Ordering. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12034. Springer, Cham. https://doi.org/10.1007/978-3-030-42058-1_38

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  • DOI: https://doi.org/10.1007/978-3-030-42058-1_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42057-4

  • Online ISBN: 978-3-030-42058-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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