@article {844,
	title = {AI and Related Technologies in the Fields of Smart Agriculture: A Review},
	journal = {Information},
	volume = {16},
	year = {2025},
	pages = {100},
	abstract = {<p>The integration of cutting-edge technologies{\textemdash}such as the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and various emerging technologies{\textemdash}is revolutionizing agricultural practices, enhancing productivity, sustainability, and efficiency. The objective of this study is to review the literature regarding the development and evolution of AI as well as other emerging technologies in the various fields of Agriculture as they are developed and transformed by integrating the above technologies. The areas examined in this study are open field smart farming, vertical and indoor farming, zero waste agriculture, precision livestock farming, smart greenhouses, and regenerative agriculture. This paper links current research, technological innovations, and case studies to present a comprehensive review of these emerging technologies being developed in the context of smart agriculture, for the benefit of farmers and consumers in general. By exploring practical applications and future perspectives, this work aims to provide valuable insights to address global food security challenges, minimize environmental impacts, and support sustainable development goals through the application of new technologies.</p>
},
	keywords = {AI, artificial intelligence, indoor farming, IoT, precision agriculture, precision livestock, regenerative agriculture, smart farming, smart green, vertical farming, zero-waste agriculture},
	issn = {2078-2489},
	doi = {https://doi.org/10.3390/info16020100},
	author = {Assimakopoulos, Fotis and Vassilakis, Costas and Margaris, Dionisis and Kotis, Konstantinos and Spiliotopoulos, Dimitris}
}
@article {842,
	title = {Artificial Intelligence Tools for the Agriculture Value Chain: Status and Prospects},
	journal = {Electronics},
	volume = {13},
	year = {2024},
	pages = {4362},
	abstract = {<p>This article explores the transformative potential of artificial intelligence (AI) tools across the agricultural value chain, highlighting their applications, benefits, challenges, and future prospects. With global food demand projected to increase by 70\% by 2050, AI technologies{\textemdash}including machine learning, big data analytics, and the Internet of things (IoT){\textemdash}offer critical solutions for enhancing agricultural productivity, sustainability, and resource efficiency. The study provides a comprehensive review of AI applications at multiple stages of the agricultural value chain, including land use planning, crop selection, resource management, disease detection, yield prediction, and market integration. It also discusses the significant challenges to AI adoption, such as data accessibility, technological infrastructure, and the need for specialized skills. By examining case studies and empirical evidence, the article demonstrates how AI-driven solutions can optimize decision-making and operational efficiency in agriculture. The findings underscore AI{\textquoteright}s pivotal role in addressing global agricultural challenges, with implications for farmers, agribusinesses, policymakers, and researchers. This article aims to advance the evolving research and discussions on sustainable agriculture, contributing insights that promote the adoption of AI technologies and influence the future of farming.</p>
},
	keywords = {artificial intelligence, precision agriculture, sustainability, value chain},
	issn = {2079-9292},
	doi = {10.3390/electronics13224362},
	author = {Assimakopoulos, Fotis and Vassilakis, Costas and Margaris, Dionisis and Kotis, Konstantinos and Spiliotopoulos, Dimitris}
}
