Готові списки джерел за темами / Intelligent food systems

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Добірка наукової літератури з теми "Intelligent food systems"

Автор: Grafiati
Опубліковано: 7 червня 2025
Оновлено: 2 серпня 2025

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Статті в журналах з теми "Intelligent food systems"

1

Corney, David. "Food bytes: intelligent systems in the food industry." British Food Journal 104, no. 10 (2002): 787–805. http://dx.doi.org/10.1108/00070700210448890.

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2

Alimgozhaev, Azamat, Gulzhan Kashaganova, and Kulzhan Togzhanova. "THE STUDY OF INTELLIGENT SYSTEMS IN INDUSTRIAL FOOD AUTOMATION." International Journal of Advanced Logistics, Transport and Engineering 5, no. 1 (2023): 30–34. http://dx.doi.org/10.52167/2790-5829-2023-5-1-30-34.

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Анотація:
In the development of an intelligent control system for basic production in the food and chemical industry, it is necessary to build an integrated and robotic control system that allows you to effectively optimize, computerize the food industry and transform food products into a clean ecological product. The main task of managing such an intelligent system is artificial intelligence, which can significantly improve packaging, increase shelf life, combine the cycle using algorithms and improve food safety by making a more transparent management system. The novelty of the article lies in the dev
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3

Sparrow, John A. "Intelligent Computer-Based Food Order-Taking Systems." Journal of Restaurant & Foodservice Marketing 1, no. 1 (1994): 21–36. http://dx.doi.org/10.1300/j061v01n01_02.

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4

Kalpana, S., S. R. Priyadarshini, M. Maria Leena, J. A. Moses, and C. Anandharamakrishnan. "Intelligent packaging: Trends and applications in food systems." Trends in Food Science & Technology 93 (November 2019): 145–57. http://dx.doi.org/10.1016/j.tifs.2019.09.008.

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5

Vyas, Sonali, Mohammad Shabaz, Prajjawal Pandit, L. Rama Parvathy, and Isaac Ofori. "Integration of Artificial Intelligence and Blockchain Technology in Healthcare and Agriculture." Journal of Food Quality 2022 (May 28, 2022): 1–11. http://dx.doi.org/10.1155/2022/4228448.

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Анотація:
Over the last decade, the healthcare sector has accelerated its digitization and electronic health records (EHRs). As information technology progresses, the notion of intelligent health also gathers popularity. By combining technologies such as the internet of things (IoT) and artificial intelligence (AI), innovative healthcare modifies and enhances traditional medical systems in terms of efficiency, service, and personalization. On the other side, intelligent healthcare systems are incredibly vulnerable to data breaches and other malicious assaults. Recently, blockchain technology has emerged
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6

de Medeiros Esper, Ian, Pål J. From, and Alex Mason. "Robotisation and intelligent systems in abattoirs." Trends in Food Science & Technology 108 (February 2021): 214–22. http://dx.doi.org/10.1016/j.tifs.2020.11.005.

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7

Abhishek, Ranvare, and Jadhav Hritvik. "Review on the Current Scenario in Active and Intelligent Packaging Technologies." Journal of Food Processing & Technology 14, no. 6 (2023): 8. https://doi.org/10.35248/2157-7110.23.14.1024.

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Анотація:
The traditional role of packaging is to provide protection from the external environment and to provide convenience in distribution. The changing global trends need innovation in the sector of food packaging. Active and intelligent packaging systems will be the innovative packaging systems of this era. In this review, we have covered the active packaging systems and intelligent packaging systems with their types. Active packaging and intelligent packaging these two terms differ from each other. The active packaging system's main objective is to extend the shelf life with the help of absorbing
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8

Ranvare, Abhishek, and Hritvik Jadhav. "Review on the Current Scenario in Active and Intelligent Packaging Technologies." Journal of Food Processing & Technology 14, no. 6 (2023): 8. https://doi.org/10.5281/zenodo.13165688.

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Анотація:
The traditional role of packaging is to provide protection from the external environment and to provide convenience in distribution. The changing global trends need innovation in the sector of food packaging. Active and intelligent packaging systems will be the innovative packaging systems of this era. In this review, we have covered the active packaging systems and intelligent packaging systems with their types. Active packaging and intelligent packaging these two terms differ from each other. The active packaging system's main objective is to extend the shelf life with the help of absorbing
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9

Lisitsyn, A. B., I. M. Chernukha, and M. A. Nikitina. "Cyber-physical systems in food production chain." Theory and practice of meat processing 8, no. 4 (2024): 316–25. http://dx.doi.org/10.21323/2414-438x-2023-8-4-316-325.

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Анотація:
The article reviews the state-of-the-science in the field of cyber-physical systems (CPSs). CPSs are intelligent systems that include physical, biological and computational components using engineering networks. CPSs are able to integrate into production processes, improve the exchange of information between industrial equipment, qualitatively transform production chains, and effectively manage business and customers. This is possible due to the ability of CPSs to manage ongoing processes through automatic monitoring and controlling the entire production process and adjusting the production to
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Muzyka, M. Y., I. G. Blagoveshchensk, V. G. Blagoveshchensk, V. V. Golovin, M. M. Blagoveshchensk, and I. A. Kachura. "Technical solutions for the implementation of a software and hardware complex for food quality management." Proceedings of the Voronezh State University of Engineering Technologies 83, no. 4 (2021): 49–56. http://dx.doi.org/10.20914/2310-1202-2021-4-49-56.

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Анотація:
The problem of technical solutions for the implementation of a software and hardware complex for food quality management is considered. The review and analysis of existing modern control systems is presented, which made it possible to conclude that today food enterprises need new effective solutions using highly efficient intelligent technologies. The analysis of the possibility of intellectualization of the food production quality management system is carried out. The main tasks of this system are presented. It is shown that a practical basis for the implementation of this problem can be the
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Дисертації з теми "Intelligent food systems"

1

Barbalho, Ingridy Marina Pierre. "Equipamento médico assistencial para monitoramento da ingestão de alimentos." Universidade Federal Rural do Semi-Árido, 2018. http://bdtd.ufersa.edu.br:80/tede/handle/tede/834.

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Submitted by Vanessa Christiane (referencia@ufersa.edu.br) on 2018-06-15T00:08:00Z No. of bitstreams: 1 IngridyMPB_DISSERT.pdf: 7607381 bytes, checksum: c08a68ab4cbff8326651716b5e44e1d8 (MD5)<br>Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2018-06-18T16:55:37Z (GMT) No. of bitstreams: 1 IngridyMPB_DISSERT.pdf: 7607381 bytes, checksum: c08a68ab4cbff8326651716b5e44e1d8 (MD5)<br>Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2018-06-18T16:56:28Z (GMT) No. of bitstreams: 1 IngridyMPB_DISSERT.pdf: 7607381 bytes, checksum: c
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Amza, Catalin Gheorghe. "Intelligent X-ray imaging inspection system for the food industry." Thesis, De Montfort University, 2002. http://hdl.handle.net/2086/10731.

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Анотація:
The inspection process of a product is an important stage of a modern production factory. This research presents a generic X-ray imaging inspection system with application for the detection of foreign bodies in a meat product for the food industry. The most important modules in the system are the image processing module and the high-level detection system. This research discusses the use of neural networks for image processing and fuzzy-logic for the detection of potential foreign bodies found in x-ray images of chicken breast meat after the de-boning process. The meat product is passed under
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3

Wong, P. C. "Flexible intelligent robot vision system for the confectionery industry." Thesis, University of Huddersfield, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.383499.

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Hesse, Max. "Reinigung 4.0 – Der Weg zur intelligenten Reinigung." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-236429.

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Анотація:
In der Lebensmittelindustrie wird heutzutage noch viel zu häufig mit überdimensionierten und ineffizienten Reinigungssystemen gearbeitet. Diese sind aus Gründen der Prozesssicherheit meist am „Worst-Case-Szenario“ ausgelegt, von bedarfsgerechter bzw. adaptiver Reinigung kann also keine Rede sein. Gründe dafür liegen vor allem am Mangel an Möglichkeiten zum Inline-Reinigungsmonitoring sowie starrer/unintelligenter Reinigungssysteme. Das Fraunhofer IVV Dresden arbeitet im Themenfeld „Adaptive Reinigung“ an verschiedenen Lösungen zur Realisierung einer bedarfsgerechten Reinigung, um eine größtmög
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5

Mumith, Jurriath-Azmathi. "Autonomous design and optimisation of a complex energy system using a reinforcement learning intelligent agent." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13661.

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Анотація:
Since the realisation of the computer, and shortly after the inception of artificial intelligence (AI), there has been an explosion of research solving human-level tasks using autonomous entities that are able to learn about an environment by observing and influencing it, known as intelligent agents (IA). This potent AI technique has yet to filter into the field of thermoscience, where the conceptual design and optimisation of complex energy systems has been a particularly challenging problem. Much of the design process still requires human expertise. But with the continual increase in computa
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6

Abarca, Tello Pedro Antonio Sebastian, and Zelada Elmer Leoncio Torres. "Factores individuales que determinan la adopción de herramientas de Business Intelligence Systems (BIS) en el mercado de las telecomunicaciones en el Perú." Bachelor's thesis, Pontificia Universidad Católica del Perú, 2021. http://hdl.handle.net/20.500.12404/20201.

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Анотація:
La presente tesis de investigación tiene como objetivo conocer los factores individuales que influyen en el uso y adopción de BIS por parte de los analistas de negocio en el sector de las telecomunicaciones. Para ello se tuvo como principales sujetos de estudio a los analistas de distintas áreas de organizaciones pertenecientes a este sector. Para lograr este objetivo, se empleó la metodología de Teoría Fundamentada (Grounded Theory). En primer lugar, se procedió con la construcción de un marco teórico que permitiera entender con claridad el fenómeno estudiado. Se empleó la técnica de revisión
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Aguilar, Acosta Milton Alberto, and Vara Juan Emilio Asto. "Modelo de Inteligencia de Negocios en la empresa “Contact Center JMT”." Master's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/655779.

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La Empresa JMT Contact Center es una empresa que se dedica al rubro de Telemarketing, Centro de Contacto y Business Process Outsourcing, con presencia en los mercados de Europa y Latinoamérica. Es una empresa en constante crecimiento y en la actualidad a pesar de estar en medio de una Pandemia ha tenido el reto de enfrentar una demanda de crecimiento en los puestos de atención. En los últimos años, la empresa ha tenido que enfrentar ciertos retos financieros ligado a los costos planificados y a los costos operativos, de tal forma que su rentabilidad como negocio se ha visto impactada, suma
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8

Benamara, Mohamed Adel. "Suivi visuel d'objets dans un réseau de caméras intelligentes : application au systèmes de manutention automatisés." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSE2136.

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L’intralogistique (ou logistique interne) s’intéresse au traitement et à l’optimisation des flux physiques au sein des entrepôts, centres de distribution et usines. Les systèmes de manutention automatisés sont au cœur de la logistique interne de plusieurs industries comme le commerce en ligne, la messagerie postale, la grande distribution, l’industrie manufacturière, le transport aéroportuaire, etc. Ces équipements composés de lignes de convoyage haute cadence permettent un transport sûr et fiable d’un volume considérable de biens et de marchandises tout en réduisant les coûts.L’automatisation
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Busacca, Fabio Antonino. "AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge." Doctoral thesis, Università degli Studi di Palermo, 2022. https://hdl.handle.net/10447/573371.

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5G-and-beyond and Internet of Things (IoT) technologies are pushing a shift from the classic cloud-centric view of the network to a new edge-centric vision. In such a perspective, the computation, communication and storage resources are moved closer to the user, to the benefit of network responsiveness/latency, and of an improved context-awareness, that is, the ability to tailor the network services to the live user's experience. However, these improvements do not come for free: edge networks are highly constrained, and do not match the resource abundance of their cloud counterparts. In such a
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Lee, Yu-Wei, and 李昱緯. "Intelligent Food Quality Control System & Automated Process Improvement." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/q4tfqx.

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碩士<br>國立東華大學<br>電機工程學系<br>100<br>This thesis focuses on the intelligent control system design and automatic process improvement of a traditional food factory. By visiting the production hardware and moving processes in their production site, we plan automated processes, production line, and standard operating procedure for them. We also implement machine learning technology to design the intelligent food quality control system, and then build the support vector regression model by production data to get the optimal production parameter suggestion. According to the experiment result, the averag
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Книги з теми "Intelligent food systems"

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Lal, Priyanka, and Pradeep Mishra, eds. Transforming Agriculture through Artificial Intelligence for Sustainable Food Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4795-8.

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2

Amza, Catalin Gheorghe. Intelligent X-ray imaging inspection system for the food industry. De Montfort University, 2002.

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3

Xu, Weiliang. Mastication Robots: Biological Inspiration to Implementation. Springer-Verlag Berlin Heidelberg, 2010.

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4

Yande, Liu, Chen Yingyi, and SpringerLink (Online service), eds. Computer and Computing Technologies in Agriculture IV: 4th IFIP TC 12 Conference, CCTA 2010, Nanchang, China, October 22-25, 2010, Selected Papers, Part III. IFIP International Federation for Information Processing, 2011.

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5

Yande, Liu, Chen Yingyi, and SpringerLink (Online service), eds. Computer and Computing Technologies in Agriculture IV: 4th IFIP TC 12 Conference, CCTA 2010, Nanchang, China, October 22-25, 2010, Selected Papers, Part II. IFIP International Federation for Information Processing, 2011.

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6

Yande, Liu, Chen Yingyi, and SpringerLink (Online service), eds. Computer and Computing Technologies in Agriculture IV: 4th IFIP TC 12 Conference, CCTA 2010, Nanchang, China, October 22-25, 2010, Selected Papers, Part I. IFIP International Federation for Information Processing, 2011.

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7

Li, Daoliang. Computer and Computing Technologies in Agriculture VI: 6th IFIP WG 5.14 International Conference, CCTA 2012, Zhangjiajie, China, October 19-21, 2012, Revised Selected Papers, Part II. Springer Berlin Heidelberg, 2013.

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8

Davenport, Thomas H., and Steven M. Miller. Working with AI. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14453.001.0001.

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Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, m
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9

Amorphous Food and Pharmaceutical Systems (Biotechnology Intelligence Unit, 281). Royal Society of Chemistry, 2003.

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10

Bonabeau, Eric, Marco Dorigo, and Guy Theraulaz. Swarm Intelligence. Oxford University Press, 1999. http://dx.doi.org/10.1093/oso/9780195131581.001.0001.

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Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science. This book pro
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Частини книг з теми "Intelligent food systems"

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Gomes, Jenifar Prantica, Imdadul Hoque, Progga Tanzin, and Nafees Mansoor. "AgriChain: Blockchain-Enabled Food Traceability." In Intelligent Sustainable Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8111-3_12.

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Arora, Anudeep, Prashant Vats, Gayatri Chopra, Ranjeeta Kaur, Davinder Singh, and Manmohan Chaudhary. "OCD: On-Demand Ordering Food Through Online Crowdsourcing." In Intelligent Sustainable Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7663-6_51.

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Natarajan, Sowmya, and Vijayakumar Ponnusamy. "Agri-Food Products Quality Assessment Methods." In Algorithms for Intelligent Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9991-7_8.

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Rahul, Kumar, Rohitash Kumar Banyal, and Hansika Sati. "ERP Module Functionalities for the Food Supply Chain Industries." In Intelligent Sustainable Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2422-3_47.

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Barman, Arpan, Amrita Namtirtha, Animesh Dutta, and Biswanath Dutta. "Food Safety Network for Detecting Adulteration in Unsealed Food Products Using Topological Ordering." In Intelligent Information and Database Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42058-1_38.

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Cevoli, Chiara, Emmanuel Purlis, and Angelo Fabbri. "Hyperspectral Imaging in the Food Industry: A Review." In Intelligent Systems Reference Library. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83127-0_10.

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Ngan, Nguyen Thi, and Bui Huy Khoi. "Using Intention of Online Food Delivery Services in Industry 4.0: Evidence from Vietnam." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_13.

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Arade, Madhuri S., and Nitin N. Pise. "Benefits, Challenges, and Future Research Directions for Blockchain-Based Agri-Food Supply Chain." In Intelligent Sustainable Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1726-6_56.

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Alsulami, Amjad, Farah Albishri, Rezan Almehmadi, Samar Alahmadi, Jawharah Albarakati, and Salma Elhag. "Six Sigma-DMAIC to Improve the Quality of Food Service: KAU Case Study." In Intelligent Sustainable Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8111-3_9.

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Campo, Paolo, Elizabeth York, Amy Woodward, Paul Krause, and Angela Druckman. "Food Incident Interactive Training Tool: A Serious Game for Food Incident Management." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47253-9_3.

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Тези доповідей конференцій з теми "Intelligent food systems"

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Vani, K. Suvarna, Praneeth Vallabhaneni, and Hema Yalavarthi. "Diabetes Prediction and Ayurvedic Food Recommendation System." In 2024 Intelligent Systems and Machine Learning Conference (ISML). IEEE, 2024. https://doi.org/10.1109/isml60050.2024.11007437.

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Jaswanth, Gaddam, Gaddam Bhargav Yadaav, and Pavithra Babu. "Food Detection and Calories Estimation using Deep Learning." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076287.

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Bae, Han-na, and Eu-tteum Baek. "Food image classification based on the Swin Transformer model." In 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS). IEEE, 2024. https://doi.org/10.1109/scisisis61014.2024.10759949.

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V, Bharanishree, S. Mohammed Mansoor Roomi, and S. Rajaram. "Food Recognition in Computer Vision: A Review of Techniques and Future Directions." In 2025 Emerging Technologies for Intelligent Systems (ETIS). IEEE, 2025. https://doi.org/10.1109/etis64005.2025.10961358.

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Bhaskar, Amisha, Rui Liu, Vishnu D. Sharma, Guangyao Shi, and Pratap Tokekar. "LAVA: Long-horizon Visual Action based Food Acquisition." In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2024. https://doi.org/10.1109/iros58592.2024.10802738.

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Jananipriya, R., and P. Ramya. "Food Hazines and Tracking System for Farmers using Blockchain Technologies." In 2025 International Conference on Intelligent Systems and Computational Networks (ICISCN). IEEE, 2025. https://doi.org/10.1109/iciscn64258.2025.10934675.

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R, Rajavarsheka, Pranitha S, Yogashree R, and P. M. Devie. "Food Spoilage Detection using Advanced Image Processing Techniques: A Multicategory Approach." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076223.

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Krishnan, Prabhakar, U. Samson Ebenezar, R. Ranitha, N. Purushotham, and T. Suresh Balakrishnan. "AI-Driven Intelligent IoT Systems for Real-Time Food Quality Monitoring and Analysis." In 2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies (TQCEBT). IEEE, 2024. http://dx.doi.org/10.1109/tqcebt59414.2024.10545305.

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Pratap, C. Benin, Aren D'Souza, Athulya Amblish, Jane Mary Mathew, Srivenu K, and Leno Varghese Babu. "Revolutionizing Culinary Quality: An Intelligent Food Grading System Employing Advanced Machine Learning Algorithms." In 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2024. http://dx.doi.org/10.1109/icaccs60874.2024.10717263.

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Naveen, Shivam, Yashvardhan Goyal, Kowsigan M, Ramamoorthy S, and Madhavan P. "The Near Optimal Identification of Food Ingredients for Enhanced Dining Experience." In 2024 International Conference on Electronic Systems and Intelligent Computing (ICESIC). IEEE, 2024. https://doi.org/10.1109/icesic61777.2024.10846198.

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Звіти організацій з теми "Intelligent food systems"

1

Short, Samuel. Alternatives to single-use plastics in food packaging and production. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.taf512.

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This rapid evidence assessment undertaken by RSM UK Consulting LLP (RSM) and Dr Samuel Short (University of Cambridge) aimed to develop an understanding of the alternatives to single-use plastics in food packaging and production in terms of their risks and opportunities, as well as potential future developments. Literature from within and beyond the UK was gathered from academic databases and reports published by government and non-governmental organisations such as environmental charities. Evidence from the literature was supplemented by findings from a workshop with experts in the field from
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2

Scarratt, Anne, and Sally Cooke. Surveillance Sampling Programme. Food Standards Agency, 2024. http://dx.doi.org/10.46756/sci.fsa.dgj755.

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3

Scarrett, Anne, and Sally Cooke. Surveillance Sampling Programme. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.svi390.

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Анотація:
This project aimed to carry out targeted surveillance sampling of retail food products for the Food Standards Agency (FSA) in order to help identify emerging food safety risks and increase the FSA’s intelligence and insight of the UK food system.
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4

Scarrett, Anne, and Sally Cooke. Retail Surveillance Sampling Programme during Covid-19 pandemic. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.zkj588.

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Анотація:
This project was commissioned to carry out targeted surveillance sampling on food products across Food Standards Agency (FSA) competent areas in order to help to identify emerging food safety risks and increase the FSA’s intelligence on the food system during the Covid-19 pandemic.
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5

Stankovic, Mirjana, and Nikola Neftenov. Cross Pollination and Digitalization of Public Sector Data: Opportunities and Challenges. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004355.

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This report aims to aid governments in Latin America and the Caribbean in embracing the opportunities public sector data utilization and artificial intelligence (AI) deployment can provide in achieving a circular economy model and the UNs Sustainable Development Goals (SDGs). For such purpose, the report provides a novel concept of sharing data between key players that we have named data cross-pollination. Drawing on this concept, it considers four SDGs, i.e., energy, sustainable food systems, reducing pollution, and smart cities. Building on case studies and initiatives, the report highlights
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6

Ampatzidis, Yiannis, Mahendra Bhandari, Andres Ferreyra, et al. AI in Agriculture: Opportunities, Challenges, and Recommendations. Chair Alex Thomasson. Council for Agricultural Science and Technology, 2025. https://doi.org/10.62300/iaag042514.

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Artificial Intelligence (AI) is rapidly being integrated into people’s lives, reshaping industries, and enabling previously unimagined innovation, even in agriculture. Generative AI focuses on creating content like text and pictures based on vast quantities of data. ExtensionBot is a generative AI platform that supports agricultural extension by providing farmers with accurate scientific information and specific recommendations. It has been shown to deliver more accurate responses to agricultural questions than broader generative AI models. Other forms of AI have been used to analyze data to p
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