基于DS2的精准农业跨数据空间互操作性
DS2-Based Cross-Data-Space Interoperability for Precision Agriculture
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中文总结 AI 辅助
本文基于Horizon Europe DS2项目，提出分层参考架构的互操作性框架，实现DigiAgro与AgroScience数据空间间安全、自主的数据共享，以生成精准农业建议，提升作物产量并保持可持续性。
中文摘要 AI 辅助
尽管现代精准农业策略致力于整合传统农业系统，但物联网数据碎片化、农民主权保护以及有限互操作性等挑战依然存在。本文介绍了我们在Horizon Europe DS2项目（DataSpace, DataShare 2.0）框架内开展的工作，该项目应用了一个面向互操作性的框架，支持不同农业数据空间的参与者在安全、主权和透明的方法下共享数据产品和服务。所提出的方法遵循分层参考架构，其中每一层由独立的操作模块组成，这些模块促进了DigiAgro和AgroScience数据空间之间的跨部门数据交换。这项工作的成果是一个自动化生态系统，用于在不同数据空间之间共享多样化的农场物联网测量数据、卫星图像和指标、天气预报以及分析服务，旨在生成关于作物实践（如灌溉计划）的准确建议，农民和农艺师将依赖这些建议来提高作物产量，同时保持可持续性。
英文摘要
Despite the strategies of modern precision agriculture to leverage the integration of legacy agricultural systems, the challenges of IoT data fragmentation, farmers' sovereignty preservation, and limited interoperability still persist. This paper presents our work, conducted within the Horizon Europe DS2 project (DataSpace, DataShare 2.0), that applies an interoperability-oriented framework supporting participants of different agricultural data spaces to share data products and services under secure, sovereign, and transparent methods. The suggested methodology follows a layered reference architecture, where each layer consists of independent operational modules that facilitate the inter-sector data exchange between DigiAgro and AgroScience Data Spaces. The result of this work is an automated ecosystem for sharing diverse farm IoT measurements, satellite images and metrics, weather forecasts, and analytics services across distinct data spaces, aiming to generate accurate recommendations on crop practices, such as irrigation schedules, that farmers and agronomists will rely on to increase crop production while maintaining sustainability.
发表机构
- University of Thessaly（色萨利大学）
- Centre for Research and Technology Hellas (CERTH)（希腊研究与技术中心）
机构由 AI 辅助整理，请以论文原文为准。
