The growing need for process visibility, sustainability and responsiveness in the agrifood sector spurs the adoption of digital technologies throughout the value chain. This paper introduces a unified cloud-edge architecture combining Internet of Things, Artificial Intelligence and Blockchain technologies to support Smart Farming and end-to-end Product Traceability Management. In contrast to existing frameworks limited to specific value chain segments, the proposed architecture enables end-to-end process integration and technological convergence within a unified digital ecosystem. It is designed to be modular, interoperable and scalable, enabling data-driven monitoring, decision-making and secure certification of agricultural practices. A real-world use case focused on olive and grape cultivation in the Apulia region demonstrates the applicability of the architecture. The use case highlights the integration of multispectral imaging on tractors, edge-side inference for crop disease detection, microservice-based orchestration in the cloud, and blockchain-backed traceability, also considering interoperability with national registries.

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A Cloud-Edge Framework Combining AI, IoT and Blockchain for Smart Farming and Agrifood Traceability

  • Saverio Ieva,
  • Luigi Pio Battista,
  • Daniele Capriuolo,
  • Armando Ciardiello,
  • Simona Petrone,
  • Gennaro Pio Auricchio,
  • Luigi Uccello

摘要

The growing need for process visibility, sustainability and responsiveness in the agrifood sector spurs the adoption of digital technologies throughout the value chain. This paper introduces a unified cloud-edge architecture combining Internet of Things, Artificial Intelligence and Blockchain technologies to support Smart Farming and end-to-end Product Traceability Management. In contrast to existing frameworks limited to specific value chain segments, the proposed architecture enables end-to-end process integration and technological convergence within a unified digital ecosystem. It is designed to be modular, interoperable and scalable, enabling data-driven monitoring, decision-making and secure certification of agricultural practices. A real-world use case focused on olive and grape cultivation in the Apulia region demonstrates the applicability of the architecture. The use case highlights the integration of multispectral imaging on tractors, edge-side inference for crop disease detection, microservice-based orchestration in the cloud, and blockchain-backed traceability, also considering interoperability with national registries.