anpcworld.com

13. JEEP INTERNATIONAL SCIENTIFIC AGRIBUSINESS CONFERENCE - MAK 2026

SMART AGRICULTURE - TECHNICAL AND ECONOMIC FACTORS OF DEVELOPMENT

Vladimir Pejanović, Goran Zarić, Radovan Pejanović

Abstracts

The authors consider the key factors in the development of smart agriculture. These are technical and socio-economic factors. Technical factors are related to scientific and technical progress and innovations. In this connection, agriculture has undergone various historical developments, i.e. the evolution of agricultural techniques. It is a long historical path from manual tools to sophisticated smart technical systems. The development of smart agriculture, however, is strongly influenced by a complex set of economic and social factors, which determine the speed and extent of its implementation. There are many risks to this development path. The authors analyze in detail certain techniques and socio-economic factors of development. In the concluding remarks, they propose a multidisciplinary approach, an integral approach and a systemic approach in the development of this important, modern stage in the development of agriculture and rural development.

Keywords

Smart agriculture, Technical factors, Socio-economic factors, Risks, Conditions of development, Future of development

References

  1. 1. Pejanović, R. (2013). Ogledi iz agrarne i ruralne ekonomije [Essays in Agrarian and Rural Economics]. Monograph. Poljoprivredni fakultet, Novi Sad, p. 634.
  2. 2. Pejanović, V. (2024). Implementation of Artificial Intelligence in Agriculture, Green Economy and Sustainable Development. In Dudić, B., Premović, J. (Eds.), Proceedings of the Fourth International Scientific Conference: Challenges of Modern Economy and Society Through the Prism of Green Economy and Sustainable Development, 268-275. Novi Sad: Faculty of Economics and Engineering Management - FIMEK. ISBN: 978-86-82408-29-1.
  3. 3. Pejanović, V. (2025). Projektovanje mernog sistema retrofitovanja u funkciji pametne poljoprivrede u konceptu Industrija 4.0. Master rad. Fakultet tehničkih nauka, Univerzitet u Novom Sadu, Republika Srbija.
  4. 4. Pejanović, V., Ergunova, O. (2025a). Smart Solutions for Climate Challenges - Application of Machine Learning in Agriculture. In B.
  5. 5. Dudić, J. Premović (Eds.), Proceedings of the Fifth International Scientific Conference: Challenges of Modern Economy and Society Through the Prism of Green Economy and Sustainable Development, 403-409, Novi Sad: Faculty of Economics and Engineering Management - FIMEK. ISBN: 978-86-82408-58-1.
  6. 6. Pejanović, V., Urekar, M. (2025b). Retrofitting Legacy Photo-Sensor Infrastructure for Hybrid Smart Agriculture and Industry 4.0. In Proceedings of the 2025 12th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN) (p. 1-6). Čačak, Serbia: IEEE. doi: 10.1109/IcETRAN66854.2025.11114313 Pejanović, V., Petrović, N., Kasapović, S., Tomić, I., Sovilj, P. (2024a). Metrology and Measurement-Information Systems in Smart Agriculture with the Application of Artificial Intelligence. In Proceedings of the Congress of Metrologists 2024 (Rad br. 28, IMEKO TC4). Palić, Subotica: Society of Metrologists - Društvo metrologa. ISBN: 978-86-906004-1-0.
  7. 7. https://drustvometrologa.org/radovi2024/28.%20TC4%20Metrology%20and%20mesurement% 20-%20information%20systems%20in%20smart%20agriculture%20with% 20the%20application%20of%20artificial%20inteleligence.pdf
  8. 8. Pejanović, V., Stanojević, B., Sovilj, P. (2024b). Implementation of a Machine Learning Method with Metrology Principles in a Simulated Computer Network. In Proceedings of the Congress of Metrologists 2024 (Rad br. 27, IMEKO TC4, TC18). Palić, Subotica: Society of Metrologists - Društvo metrologa. ISBN: 978-86-906004-1-0. https://drustvometrologa.org/radovi2024/27.%20TC4%20TC18%20Implementation%20of%20 a%20machine%20learning%20method%20wirh%20metrology%20principles%20in%20a%20s imulated%20computer%20network.pdf
  9. 9. Villa-Henriksen, A., Edwards, G.T., Pesonen, L.A., Green, O., Sørensen, C.A.G. (2020). Internet of Things in arable farming: Implementation, applications, challenges and potential. Biosystems Engineering, 191, 60-84. doi.org/10.1016/j.biosystemseng.2020.01.004