INNOVATIVE APPROACHES TO THE IMPLEMENTATION OF DIGITAL PLATFORMS IN AGRICULTURE AND PERSONNEL TRAINING
DOI:
https://doi.org/10.60078/3060-4842-2026-vol3-iss3-pp664-705Abstract
Today, the acceleration of digitalization processes in agriculture is increasing the need to provide representatives of the industry, in particular farmers, with modern knowledge and skills. Therefore, expanding digitalization in farms, improving farmers' knowledge and skills in digital platforms is considered one of the promising areas of agricultural development. This article analyzes the acceleration of digitalization processes in farms, modern digital platforms used in training farmers, innovative approaches and their practical effectiveness. During the study, the importance of online educational platforms, mobile applications, video lessons, webinars, smart agroplatforms and IoT technologies in the activities of farmers was studied. The analysis showed that digital platforms allow farmers to quickly and conveniently obtain information about drip irrigation, fertilization systems, disease and pest control, intensive gardening and water-saving technologies. The article also highlights the opportunities for farmers to plan agrotechnical activities, increase productivity and use resources efficiently using digital platforms. It is noted that using IoT sensors and smart monitoring systems, soil moisture, air temperature and plant condition can be monitored remotely, which helps reduce crop losses. It is also noted that agro-platforms based on artificial intelligence help farmers make quick and accurate decisions
Keywords:
digital platforms innovative agro-technologies smart agriculture IoT technologies agro-platform online education digital monitoring digitalization of agriculture artificial intelligence mobile applications intensive gardening water-saving technologies agrodrone webinar smart monitoring systemsReferences
Abbasi, R., Martinez, P., & Ahmad, R. (2022). The digitization of agricultural industry – a systematic literature review on agriculture 4.0. Smart Agricultural Technology. https://doi.org/10.1016/j.atech.2022.100042.
Beglayev, U., Boltayev, N., Isakhodjaeva, S., & Rakhmatova, J. (2025). Increase of the efficiency of distance learning in the field of agribusiness and e-commerce. IOP Conference Series: Earth and Environmental Science, 1535. https://doi.org/10.1088/1755-1315/1535/1/012027.
Bhaskara, S., & Bawa, K. (2021). Societal Digital Platforms for Sustainability: Agriculture. Sustainability, 13, 5048. https://doi.org/10.3390/su13095048.
Chang, J., Chiu, P., & Lai, C. (2020). Implementation and evaluation of cloud-based e-learning in agricultural course. Interactive Learning Environments, 31, 908 - 923. https://doi.org/10.1080/10494820.2020.1815217.
Gong, S., Jiang, L., & Yu, Z. (2025). Can Digital Human Capital Promote Farmers’ Willingness to Engage in Green Production? Exploring the Role of Online Learning and Social Networks. Behavioral Sciences, 15. https://doi.org/10.3390/bs15020227.
Kumar, S., Suriyan, K., Jacob, A., Varghese, A., & Francis, E. (2025). Smart farming for a sustainable future: implementing IoT-based systems in precision agriculture. Bulletin of the National Research Centre, 49. https://doi.org/10.1186/s42269-025-01366-8.
Mansoor, S., Iqbal, S., Popescu, S., Kim, S., Chung, Y., & Baek, J. (2025). Integration of smart sensors and IOT in precision agriculture: trends, challenges and future prospectives. Frontiers in Plant Science, 16. https://doi.org/10.3389/fpls.2025.1587869.
O., M., Alam, A., & Hotak, Y. (2025). Smart Sensor Technologies Shaping the Future of Precision Agriculture: Recent Advances and Future Outlooks. Journal of Sensors, 2025. https://doi.org/10.1155/js/2460098.
Rajak, P., Ganguly, A., Adhikary, S., & Bhattacharya, S. (2023). Internet of things and smart sensors in agriculture: Scopes and challenges. Journal of Agriculture and Food Research. https://doi.org/10.1016/j.jafr.2023.100776.
Saha, G., Shahrin, F., Khan, F., Meshkat, M., & Azad, A. (2025). Smart IoT-driven precision agriculture: Land mapping, crop prediction, and irrigation system. PLOS One, 20. https://doi.org/10.1371/journal.pone.0319268.
Shaikh, T., Rasool, T., & Lone, F. (2022). Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming. Comput. Electron. Agric., 198, 107119. https://doi.org/10.1016/j.compag.2022.107119.
Sher, A., Mazhar, S., Rahut, D., & Yuan, H. (2025). Leveraging internet use for sustainable agriculture: the impact of digital training on adoption of energy-smart agricultural practices and welfare. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-16804-w.
Soussi, A., Zero, E., Sacile, R., Trinchero, D., & Fossa, M. (2024). Smart Sensors and Smart Data for Precision Agriculture: A Review. Sensors (Basel, Switzerland), 24. https://doi.org/10.3390/s24082647.
Spyrou, O., Ariza-Sentís, M., & Vélez, S. (2025). Enhancing Education in Agriculture via XR-Based Digital Twins: A Novel Approach for the Next Generation. Applied System Innovation. https://doi.org/10.3390/asi8020038.
Sun, X., Chen, H., Wang, Q., & Liu, X. (2021). Research and Design of Online Training Platform based on Spring Cloud Distributed System Structure and Computer Big Data. Journal of Physics: Conference Series, 1952. https://doi.org/10.1088/1742-6596/1952/4/042087.
Ubaydullayeva, S., Ubaydullayeva, D., Gaziyeva, R., Gulyamova, Z., Tadjiyeva, G., & Kadirova, N. (2022). Model of Organizing Online Learning for Students in Agricultural Area. 2022 2nd International Conference on Technology Enhanced Learning in Higher Education (TELE), 317-320. https://doi.org/10.1109/tele55498.2022.9800945.
Waqas, M., Naseem, A., Humphries, U., Hlaing, P., Dechpichai, P., & Wangwongchai, A. (2025). Applications of machine learning and deep learning in agriculture: A comprehensive review. Green Technologies and Sustainability. https://doi.org/10.1016/j.grets.2025.100199.
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