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<p>Agriculture is undergoing rapid digital transformation to address climate change, resource scarcity, and rising food demand. Digital convergence enables real-time monitoring, predictive analytics, automation, and traceability, enhancing productivity, sustainability, and system resilience. This structured and critical literature review synthesizes recent advancements and proposes an integrative framework encompassing six core technological domains: Sensors and IoT, Geographic Information Systems (GIS), Satellite Imagery and Drones, Artificial Intelligence and Machine Learning, Robotics and Automation, and Blockchain. Beyond classification, the study analyzes cross-domain interdependencies and identifies convergence mechanisms that support precision agriculture, automation, and supply-chain transparency. A central contribution is a multi-layered conceptual model organized into five hierarchical levels: (1) infrastructure (sensing, connectivity, data acquisition), (2) geospatial contextualization, (3) intelligence (AI-driven analytics), (4) physical execution (robotic and automated systems), and (5) governance and trust (blockchain-enabled traceability). This layered architecture formalizes digital convergence as a coordinated cyber-physical ecosystem, advancing the conceptual evolution from Agriculture 4.0 toward an integrative Agriculture 5.0 paradigm capable of adaptive, real-time decision-making.</p>

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Digital Convergence in Agriculture: A Review and Integrative Framework for Emerging Technologies

  • 期刊论文

  • 发表日期：

    2026年8月5日

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  • Alan Diaz-Manriquez,
  • Vicente Paul Saldivar-Alonso,
  • Juan Carlos Elizondo-Leal,
  • Jose Ramon Martinez-Angulo,
  • Jose David Filoteo-Razo

摘要

Agriculture is undergoing rapid digital transformation to address climate change, resource scarcity, and rising food demand. Digital convergence enables real-time monitoring, predictive analytics, automation, and traceability, enhancing productivity, sustainability, and system resilience. This structured and critical literature review synthesizes recent advancements and proposes an integrative framework encompassing six core technological domains: Sensors and IoT, Geographic Information Systems (GIS), Satellite Imagery and Drones, Artificial Intelligence and Machine Learning, Robotics and Automation, and Blockchain. Beyond classification, the study analyzes cross-domain interdependencies and identifies convergence mechanisms that support precision agriculture, automation, and supply-chain transparency. A central contribution is a multi-layered conceptual model organized into five hierarchical levels: (1) infrastructure (sensing, connectivity, data acquisition), (2) geospatial contextualization, (3) intelligence (AI-driven analytics), (4) physical execution (robotic and automated systems), and (5) governance and trust (blockchain-enabled traceability). This layered architecture formalizes digital convergence as a coordinated cyber-physical ecosystem, advancing the conceptual evolution from Agriculture 4.0 toward an integrative Agriculture 5.0 paradigm capable of adaptive, real-time decision-making.