Abstract
According to the International Organization for Standardization (ISO), traceability in the agriculture sector is the ability to follow the movement of a feed or food through specified stage(s) of production, processing, and distribution [1]. By deploying smart contracts on the Ethereum blockchain, A web3 modular model has been implemented to enable real-time data acquisition, monitoring, and storage of the key food supply chain movements on a tamper-proof public blockchain. This solution assists each participant in transacting with other FSC stakeholders. In order to collect vital data about food status, such as temperature, humidity, and food location without human involvement, IoT networks are implemented in different locations within the supply chain to ensure transparency and data integrity, Finlay, machine learning models are established through training based on various datasets, including meteorological data, to ensure accuracy in the collected data and aid in decision-making. This paper outlines the architecture and implementation of this solution.
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Addou, K., El Ghoumari, M.Y., Archdir, S., Azouazi, M. (2024). A Web3 Model Boosted by IoT and Machine Learning to Bring Transparency and Sustainability to the Food Supply Chain. In: Ezziyyani, M., Kacprzyk, J., Balas, V.E. (eds) International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD'2023). AI2SD 2023. Lecture Notes in Networks and Systems, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-031-54318-0_3
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