IoT-based urban agriculture container farm design and implementation for localized produce supply

He, Leilei; Fu, Longsheng; Fang, Wentai; Sun, Xiaoming; Suo, Rui; Guo, Li; Zhao, Guanao; Yang, Ruizhe; Li, Rui

doi:10.1016/j.compag.2022.107445

Cited by 10 publications

(2 citation statements)

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“…The results of this study allow us to positively assess the prospects of LLM and RAG for creating decision support systems that will work like an experienced subject matter expert -recognizing a complex situation, proposing solution options for this situation and answering additional questions from the user, including explaining the proposed solutions. Today in Agriculture much attention is paid to the application of AI and, in particular, neural networks for automatic recognition of plant diseases, pests or classification of agricultural products [16][17][18][19][20]. The proposed approach allows to complement these tools with new capabilities.…”

Section: Discussionmentioning

confidence: 99%

Decision support in a smart greenhouse using large language model with retrieval augmented generation

Glukhikh,

Chernysheva,

Shentsov

2024

Third International Conference on Digital Technologies, Optics, and Materials Science (DTIEE 2024)

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The paper discusses the application of large language models for the development of decision support systems, particularly in the agro-industry. The thesis that decision support is necessary in the sphere of agriculture is confirmed. In order to optimize the activity of smart greenhouses it is reasonable to implement information systems and technologies using large language models. The architecture of decision support system with Retrieval Augmented Generation technology for controlling disease incidence of plants cultivated is proposed. Experiments with the implemented decision support system have been carried out. It is concluded that the application of large language models in the operation of smart greenhouses is promising for use in agriculture in general.

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Section: Discussionmentioning

confidence: 99%

Decision support in a smart greenhouse using large language model with retrieval augmented generation

Glukhikh,

Chernysheva,

Shentsov

2024

Third International Conference on Digital Technologies, Optics, and Materials Science (DTIEE 2024)

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“…The authors proposed a method in which a farm's environment would be remotely monitored and controlled by an Internet of Things (IoT) management system [18]. The container farm was set up in an outside parking area as a case study for urban agriculture, using mushrooms as a test crop.…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Study on Iot, Artificial Intelligence, Wireless Sensor Networks, and Robotics in Agriculture

2023

IRJMETS

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Agriculture is the primary source of food for the globe, but it is currently confronting significant challenges due to rising consumer demand, worries about food safety and security, and requests for environmental protection, water conservation, and long-term sustainability. The demand for technologies that offers substantial cost savings, prediction of crop diseases & feasible solutions to protect the crop, improved operational efficiency, and better profitability is raising exponentially. Digital agriculture management applications have advanced significantly, influencing Information and Communication Technology (ICT) to provide advantages for farmers and consumers as well as pushing technological solutions into rural areas. The system which performs operations like ploughing, sowing, cutting, fertilization, and navigation at an affordable price is the need of the hour. The study discusses the potential of ICT technologies in conventional agriculture as well as potential difficulties that could occur when they are used to farming practises. The roles of robots, Internet of Things (IoT), and Artificial Intelligence (AI) in agriculture are explored in detail. This detailed analysis concludes the current and future trends in technologies to uplift the life of farmers.

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Design and implementation of a cost-aware and smart oyster mushroom cultivation system

Elewi,

Hajhamed,

Khankan

et al. 2024

Smart Agricultural Technology

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IoT-based urban agriculture container farm design and implementation for localized produce supply

Cited by 10 publications

References 11 publications

Decision support in a smart greenhouse using large language model with retrieval augmented generation

Decision support in a smart greenhouse using large language model with retrieval augmented generation

A Comprehensive Study on Iot, Artificial Intelligence, Wireless Sensor Networks, and Robotics in Agriculture

Design and implementation of a cost-aware and smart oyster mushroom cultivation system

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