面向可持续与精准农业的万物互联（IoE）
Sustainable and Precision Agriculture with the Internet of Everything (IoE)
AI总结：
本文探讨万物互联（IoE）在精准农业中的变革作用，整合分子通信、纳米物联网等子领域，结合6G、区块链和机器学习，提升作物监测与资源管理，实现分子和生物尺度的精准农业。
摘要：
农业面临着人口增长、资源稀缺和气候变化带来的严峻挑战，推动其向先进的技术集成型耕作方式转变。机械化已改变了农业，提高了可持续性和作物生产力。如今，人工智能（AI）、机器人技术、生物技术、区块链和物联网（IoT）等技术正在推进精准农业。万物互联（IoE）的概念因其整合各种物联网专业化领域（称为IoX，其中X指特定领域）的整体性方法而受到关注。本文探讨了IoE在农业中的变革性作用，超越了传统IoT应用，整合了分子通信（MC）、纳米物联网（IoNT）、生物纳米物联网（IoBNT）、设计噬菌体和真菌物联网（IoF）等细分领域。我们的研究详细回顾了这些IoE子领域与6G、区块链和机器学习（ML）相结合，如何在作物监测、资源管理和病害控制等领域增强精准农业。与以往以IoT为中心的综述不同，本研究独特地聚焦于IoE在分子和生物尺度上推进农业的潜力，实现更精准的资源利用和韧性。主要贡献包括探索这些技术的适用性、相关挑战以及精准农业未来研究方向的建议。
英文摘要：
Agriculture faces critical challenges from population growth, resource scarcity, and climate change, driving a shift toward advanced, technology-integrated farming. Mechanization has transformed agriculture, enhancing sustainability and crop productivity. Now, technologies like artificial intelligence (AI), robotics, biotechnology, blockchain, and the Internet of Things (IoT) are advancing precision agriculture. The concept of the Internet of Everything (IoE) has gained traction due to its holistic approach to integrating various IoT specializations, called IoXs with X referring to a specific domain. This paper explores the transformative role of IoE in agriculture, expanding beyond traditional IoT applications to integrate niche subdomains like molecular communication (MC), the Internet of Nano Things (IoNT), the Internet of Bio-Nano Things (IoBNT), designer phages, and the Internet of Fungus (IoF). Our study provides a detailed review of how these IoE subdomains, in conjunction with 6G, blockchain, and machine learning (ML), can enhance precision farming in areas like crop monitoring, resource management, and disease control. Unlike prior IoT centric reviews, this work uniquely focuses on IoEs potential to advance agriculture at molecular and biological scales, achieving more precise resource utilization and resilience. Key contributions include an exploration of these technologies applicability, associated challenges, and recommendations for future research directions within precision agriculture.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
