数字化背景下基于边缘计算驱动的智慧农业

Smart Agriculture Driven by Edge Computing under the Digital Background

摘要:

数字经济的迅猛发展，以人工智能、云计算和大数据为核心的新一代信息技术正在全球范围内崭露头角，深刻影响着经济和人们的生活。这一变革潮流同时推动着经济社会发展和技术范式的变迁，对农业生产方式进行了根本性的改革。农业生产经历了手工劳动、机械化和简单自动化时期，如今正逐步步入以新一代信息技术为核心、数据为主要驱动力的数字时代。在这一背景下，本文建立了基于边缘计算的智能农业供应链机制。边缘计算作为有前景的范式，在解决农业数据处理和决策制定挑战方面显得尤为重要。通过将计算靠近数据源，边缘计算实现了对农业数据的实时处理和分析，从而降低了延迟，提高了响应速度。实证验证结果显示，集成的边缘智能支柱实现了显著的分析增强，同时最大限度地降低了成本，展示了系统范围的数据到决策的转换。该技术的实证验证也证实了协同效应带来的相当大的效率。除了对生产力的提升，本文研究还关注了通过优化资源利用实现的环境可持续性的增强。深入理解新兴技术，特别是边缘计算在农业中的应用，强调了透明系统的实施对提高农业网络中的可见性的重要性，并指出去中心化的架构在克服基础设施限制方面的鲁棒性。这项研究为农产品市场的稳定性和可持续性提供了有益的参考，为未来智慧农业供应链的发展提供了有力的支持。

Abstract:

The rapid development of the digital economy, with artificial intelligence, cloud computing, and big data as its core, is emerging globally, profoundly impacting the economy and people"s lives. This wave of transformation is driving both economic and social development and a shift in technological paradigms, fundamentally reforming agricultural production methods. Agricultural production has undergone periods of manual labor, mechanization, and simple automation, and is now gradually entering the digital era with the core focus on new-generation information technology and data. Against this backdrop, this paper establishes an intelligent agricultural supply chain mechanism based on edge computing. Edge computing, as a promising computing paradigm, proves crucial in addressing challenges related to agricultural data processing and decision-making. By bringing computation closer to data sources, edge computing achieves real-time processing and analysis of agricultural data, reducing latency and enhancing response speed. Empirical validation results demonstrate that the integrated edge intelligence pillar significantly enhances analytical capabilities while minimizing costs, showcasing an efficient transformation of data into decisions at the system level. The empirical application of this technology also confirms considerable efficiency gains through synergistic effects. In addition to productivity gains, this study also emphasizes the improvement of environmental sustainability through optimized resource utilization. A comprehensive understanding of emerging technologies, particularly the application of edge computing in agriculture, underscores the importance of implementing transparent systems to enhance visibility in agricultural networks. Furthermore, the study points out the robustness of decentralized architectures in overcoming infrastructure limitations. This research provides valuable insights for the stability and sustainability of agricultural markets and offers robust support for the future development of smart agricultural supply chains.