Artificial Intelligence in Agriculture and Smart Agriculture: Poster Designs in the Context of Digital Transformation for Sustainability
DOI:
https://doi.org/10.64293/mentor.v2i4.45Keywords:
Smart Agriculture, Artificial Intelligence, Sustainability, Digital TransformationAbstract
One of the fundamental components of sustainable agriculture, smart farming plays a significant role in preserving natural resources, increasing productivity, and minimizing environmental impacts. Artificial intelligence improves decision-making processes in agriculture through applications such as monitoring soil health, predicting crop yields, controlling pests, and optimizing the use of water and fertilizers. Furthermore, these technologies, combined with autonomous tractors, agricultural robots, drones, and the Internet of Things (IoT) systems, provide efficiency and cost savings. This study examines the potential of artificial intelligence to ensure sustainability in the agricultural sector and provide innovative solutions to the challenges encountered. In this context, artificial intelligence applications in agriculture and their future contributions to sustainable development are explored. Finally, a series of posters reflecting artificial intelligence and digital technologies used in agriculture were designed, and these posters were explained in terms of both content and design.
References
Alam, M., & Khan, I. R. (2022). Application of AI in smart cities. In Industrial Transformation (61-86). CRC Press. DOI: https://doi.org/10.1201/9781003229018-4
Balyan, S., Jangir, H., Tripathi, S. N., Tripathi, A., Jhang, T., & Pandey, P. (2024). Seeding a Sustainable Future: Navigating the Digital Horizon of Smart Agriculture. Sustainability, 16(2), 475. DOI: https://doi.org/10.3390/su16020475
Bist, A. S., Agarwal, V., Aini, Q., & Khofifah, N. (2022). Managing Digital Transformation in Marketing:" Fusion of Traditional Marketing and Digital Marketing". International Transactions on Artificial Intelligence, 1(1), 18-27. DOI: https://doi.org/10.34306/italic.v1i1.86
Buttar, N. A., Waqas, M. M., Muthmainnah, M., Omer, M. M., Niaz, Y., & Khang, A. (2023).
Robotic Innovations in Agriculture. Handbook of Research on AI-Equipped IoT Applications in High-Tech Agriculture, 131.
Choi, T., Park, J., Kim, J. J., Shin, Y. S., & Seo, H. (2022). Work efficiency analysis of multiple heterogeneous robots for harvesting crops in smart greenhouses. Agronomy, 12(11), 2844. DOI: https://doi.org/10.3390/agronomy12112844
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International journal of information management, 48, 63-71. DOI: https://doi.org/10.1016/j.ijinfomgt.2019.01.021
Huseynova, A., Yasin, R & Atif, M. (2023). Green human resource management, a gateway to employer branding: Mediating role of corporate environmental sustainability and corporate social sustainability. Corporate Social Responsibility and Environmental Management, 30(1), 369-383. DOI: https://doi.org/10.1002/csr.2360
Javaid, M., Haleem, A., Khan, I. H., & Suman, R. (2023). Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Advanced Agrochem, 2(1), 15-30. DOI: https://doi.org/10.1016/j.aac.2022.10.001
Jha, C. K., Singh, V., Stevanovic, M., Dietrich, P., Saxena, S., Mosnier, A., ... & Schmidt-traub, G. (2021). Pathways to sustainable land-use and food systems in India by 2050.
Khakurel, J., Penzenstadler, B., Porras, J., Knutas, A., & Zhang, W. (2018). The rise of artificial intelligence under the lens of sustainability. Technologies, 6(4), 1-18. DOI: https://doi.org/10.3390/technologies6040100
Koshariya, A. K., Kalaiyarasi, D., Jovith, A. A., Sivakami, T., Hasan, D. S., & Boopathi, S. (2023). Ai-enabled iot and wsn-integrated smart agriculture system. In Artificial Intelligence Tools and Technologies for Smart Farming and Agriculture Practices (200-218). IGI Global. DOI: https://doi.org/10.4018/978-1-6684-8516-3.ch011
Kurniawan, F. Y., & Santoso, A. D. (2020). Stomata profile comparisons in abaxial and adaxial zones of dendrobium aphyllum and arachnis flos-aeris leaves. Biota: Biologi dan Pendidikan Biologi, 13(2), 103-113. DOI: https://doi.org/10.20414/jb.v13i2.310
Lutfiani, N., & Meria, L. (2022). Utilization of big data in educational technology research. International Transactions on Education Technology, 1(1), 73-83. DOI: https://doi.org/10.34306/itee.v1i1.198
Manongga, N. H., Deta, H. U., & Winarso, A. (2022). Health Status of Sacrificial Animals in Kupang City in 2020 Based on Anthemortem and Postmortem Examination. Jurnal Veteriner Nusantara, 5(2), 34-41. DOI: https://doi.org/10.35508/jvn.v5i2.4254
McClure, L. A., LeBlanc, W. G., Fernandez, C. A., Fleming, L. E., Lee, D. J., Moore, K. J., & Caban-Martinez, A. J. (2017). Green collar workers: an emerging workforce in the environmental sector. Journal of occupational and environmental medicine, 59(5), 440-445. DOI: https://doi.org/10.1097/JOM.0000000000000986
Özgüven, M. M. (2023). Bahçe Bitkileri Yetiştiriciliğinde Kullanılan Dijital Tarım Teknolojileri. Tarım Makinaları Bilimi Dergisi, 19(3), 174-193.
Pakdemirli, B., Birişik, N., Aslan, İ., Sönmez, B., & Gezici, M. (2021). Türk Tarımında Dijital Teknolojilerin Kullanımı ve Tarım-Gıda Zincirinde Tarım 4.0. Toprak Su Dergisi, 10(1), 78-87. DOI: https://doi.org/10.21657/topraksu.898774
Quy, V. K., Hau, N. V., Anh, D. V., Quy, N. M., Ban, N. T., Lanza, S., ... & Muzirafuti, A. (2022). IoT-enabled smart agriculture: architecture, applications, and challenges. Applied Sciences, 12(7), 3396. DOI: https://doi.org/10.3390/app12073396
Ryan, M., Isakhanyan, G., & Tekinerdogan, B. (2023). An interdisciplinary approach to artificial intelligence in agriculture. NJAS: Impact in Agricultural and Life Sciences, 95(1), 2168568. DOI: https://doi.org/10.1080/27685241.2023.2168568
Sarkar, U., Banerjee, G., & Ghosh, I. (2022). Artificial intelligence in agriculture: Application trend analysis using a statistical approach. International Journal of Applied Science and Engineering, 20(1), 1-8. DOI: https://doi.org/10.6703/IJASE.202303_20(1).002
Şahin, H. (2022). Dijital tarım, Tarım 4.0, akıllı tarım, robotik uygulamalar ve otonom sistemler. Tarım Makinaları Bilimi Dergisi, 18(2), 68-83.
Şahin, H. (2024). Tarımsal Akıllı Sulama Sistemlerinde Yapay Zekâ, Derin Öğrenme ve Nesnelerin İnterneti Uygulamaları. Tarım Makinaları Bilimi Dergisi, 20(1), 41-60.
Villanova-Solano, C., Díaz-Peña, F. J., Hernández-Sánchez, C., González-Sálamo, J., Edo, C., Vega-Moreno, D.,& Hernández-Borges, J. (2024). Beneath the water column: Uncovering microplastic pollution in the sublittoral coastal sediments of the Canary Islands, Spain. Journal of Hazardous Materials, 465, 133128. DOI: https://doi.org/10.1016/j.jhazmat.2023.133128
Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., ... & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature communications, 11(1), 1-10. DOI: https://doi.org/10.1038/s41467-019-14108-y
Zhang, X., Guo, Y., Yang, J., Li, D., Wang, Y., & Zhao, R. (2022). Many-objective evolutionary algorithm based agricultural mobile robot route planning. Computers and Electronics in Agriculture, 200, 107274. DOI: https://doi.org/10.1016/j.compag.2022.107274
Zidan, F., & Febriyanti, D. E. (2024). Optimizing Agricultural Yields with Artificial Intelligence-Based Climate Adaptation Strategies. IAIC Transactions on Sustainable Digital Innovation (ITSDI), 5(2), 136-147. DOI: https://doi.org/10.34306/itsdi.v5i2.663
Downloads
Published
Versions
- 2026-03-03 (2)
- 2026-03-03 (1)
How to Cite
Issue
Section
License
Copyright (c) 2026 Eda Sezerer Albayrak, Büşra Maden, Çağrı Gümüş
This work is licensed under a Creative Commons Attribution 4.0 International License.
