Abstract: Traceability in food supply chains is crucial for ensuring safety, enabling effective quality control, and maintaining consumer trust. However, traditional paper-based or digital tracking systems often prove too slow and opaque during food safety incidents or investigations into fraud. To address these limitations, this paper presents a modular Web3 architecture that integrates Ethereum blockchain smart contracts, Internet of Things (IoT) sensors, and machine learning (ML) to achieve end-to-end traceability and sustainability in agrifood supply chains, and to support auditable, partially automated decision-making. The system design separates concerns into layers: an on-chain layer of Ethereum smart contracts for tamper-proof event logging and automated business logic, and an off-chain layer for secure storage of detailed sensor data and documents, linked by crypto-graphic hashes to ensure data provenance. Low-cost IoT sensors are deployed from farm to distributor, continuously monitoring environmental conditions (temperature, humidity, geolocation) and uploading signed, time-stamped summaries to the blockchain. In addition, ML models perform predictive quality control by estimating expected conditions, detecting anomalies, and scoring the conformity of product batches, which enables smart contracts to automatically trigger state transitions (acceptance or dispute escrow of shipments) based on real-time data. Using Ethereum smart contracts, a prototype that manages the life cycle of a specific food product was implemented, and two cases (conformant vs non-conformant shipments) were studied to demonstrate how cryptographically verifiable data and events make decisions transparent and trustworthy.

Addou Kamal and Mohammed Yassine El Ghoumari. “Ensuring End-to-End Traceability and Sustainability in the FSC: A Modular Web3 Architecture Integrating Blockchain, IoT, and Machine Learning”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.11 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161196

@article{Kamal2025,
title = {Ensuring End-to-End Traceability and Sustainability in the FSC: A Modular Web3 Architecture Integrating Blockchain, IoT, and Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161196},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161196},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {11},
author = {Addou Kamal and Mohammed Yassine El Ghoumari}
}