你想知道的关于智慧农业的一切
Everything You wanted to Know about Smart Agriculture
摘要：
预计到2050年，世界人口将增加近20亿，导致粮食需求迅速增加。最近的一项预测表明，尽管取得了一些进展，但世界在实现“零饥饿”目标方面仍处于落后状态。社会经济和福祉的后果将影响粮食安全。弱势群体将遭受营养不良。为了满足不断增长的人口的需求，农业需要现代化，变得智能化和自动化。传统农业可以通过采用现有技术改造为高效、可持续、生态友好的智慧农业。在这篇调查论文中，作者介绍了智能农业的应用、技术趋势、可用数据集、网络选项和挑战。农业网络物理系统是如何建立在互联网的农业物联网通过各种应用领域进行了讨论。农业4.0也是一个整体。我们专注于支持自动化的人工智能（AI）和机器学习（ML）等技术，以及提供数据完整性和安全性的分布式账本技术（DLT）。在深入研究了不同的体系结构之后，我们还提出了一个依赖于数据处理位置的智能农业框架。我们将智能农业的开放研究问题分为两组-从技术角度和网络角度。AI、ML、作为DLT的区块链以及基于物理不可克隆功能（PUF）的硬件安全属于技术组，而任何与网络相关的攻击、虚假数据注入和类似威胁都属于网络研究问题组。
英文摘要：
The world population is anticipated to increase by close to 2 billion by 2050 causing a rapid escalation of food demand. A recent projection shows that the world is lagging behind accomplishing the "Zero Hunger" goal, in spite of some advancements. Socio-economic and well being fallout will affect the food security. Vulnerable groups of people will suffer malnutrition. To cater to the needs of the increasing population, the agricultural industry needs to be modernized, become smart, and automated. Traditional agriculture can be remade to efficient, sustainable, eco-friendly smart agriculture by adopting existing technologies. In this survey paper the authors present the applications, technological trends, available datasets, networking options, and challenges in smart agriculture. How Agro Cyber Physical Systems are built upon the Internet-of-Agro-Things is discussed through various application fields. Agriculture 4.0 is also discussed as a whole. We focus on the technologies, such as Artificial Intelligence (AI) and Machine Learning (ML) which support the automation, along with the Distributed Ledger Technology (DLT) which provides data integrity and security. After an in-depth study of different architectures, we also present a smart agriculture framework which relies on the location of data processing. We have divided open research problems of smart agriculture as future research work in two groups - from a technological perspective and from a networking perspective. AI, ML, the blockchain as a DLT, and Physical Unclonable Functions (PUF) based hardware security fall under the technology group, whereas any network related attacks, fake data injection and similar threats fall under the network research problem group.
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。
