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Smart farming has the potential to deliver substantial long-term benefits, such as efficient water management, climate change resilience, increased productivity, and improved agricultural sustainability. However, its adoption remains low in many regions due to barriers such as high setup costs, lack of technical skills, and persistent concerns over data ownership and sharing. While many studies have examined the factors influencing smart farming adoption across various agricultural scenarios, existing solutions for collaborative data sharing remain inadequate, fragmented, narrowly scoped, or overly centralized, and none provides a concrete, scalable and secure framework for collaborative data sharing across heterogeneous data systems. Such data sharing is foundational for sustainable agriculture, enabling real-time decision-making, regional resource coordination, and precision irrigation management. The proposal presents a novel, integrated blockchain-based system for secure and verifiable cross-organizational data sharing to support smart irrigation in agriculture. It combines blockchain smart contracts, Decentralized Identifiers (DIDs), Zebra Capability Tokens (ZCAPs) and Verifiable Credentials (VCs) within a Self-Sovereign Identity (SSI) framework to enable fine-grained access control and trustless authentication without relying on a trusted third party. To address interoperability across heterogeneous agricultural databases, the study introduces a data probe layer that links distributed agricultural data sources, standardizes their formats, and enables controlled and traceable data exchange without altering the original data structures. To demonstrate the operational feasibility of the proposed approach, a real-world scenario for secure weather data sharing is implemented. This scenario relies on locally installed Davis Vantage Pro2 stations and external weather data APIs with satellite-enhanced inputs. Farms can access high-resolution local weather data even without their own station, thanks to a controlled sharing mechanism. If local stations are unavailable in a specific area, the system automatically switches to external weather sources. Robustness and operational efficiency are validated in this use case. The framework is designed to be fully scalable and allows for the integration of additional sensitive agricultural datasets. By enabling secure, responsible and controlled data sharing among farms, organizations and stakeholders, collaborative innovation and data-driven policymaking are supported, laying the foundation for a smart, sustainable and resilient agricultural ecosystem.
Amraouy et al. (Fri,) studied this question.