Dimensions and main elements of data-driven agriculture

Authors

  • Ali Bakhshi Movahed Iran university of science and technology, Tehran, Iran

Keywords:

Smart agriculture, data-driven agriculture, sensor-based wireless network

Abstract

Big data is a vast collection of structured and unstructured data that can be extracted and used to analyze information and build predictive systems for better decision making. Telecommunications, healthcare, marketing, education and many other applications including There are cases that are widely used in the use of big data in agriculture. Technologies such as livestock monitoring tools, unmanned aerial vehicles and soil sensors are constantly generating large volumes of data to support data-driven agriculture. In this chapter, the most important applications of big data in data-driven agriculture are examined.

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References

Aliahmadi, A., & Nozari, H. (2023, January). Evaluation of security metrics in AIoT and blockchain-based supply chain by Neutrosophic decision-making method. In Supply Chain Forum: An International Journal (Vol. 24, No. 1, pp. 31-42). Taylor & Francis.

Aliahmadi, A., Jafari-Eskandari, M., Mozafari, M., & Nozari, H. (2013). Comparing artificial neural networks and regression methods for predicting crude oil exports. International Journal of Information, Business and Management, 5(2), 40-58.

Aliahmadi, A., Movahed, A. B., & Nozari, H. (2024). Collaboration Analysis in Supply Chain 4.0 for Smart Businesses. In Building Smart and Sustainable Businesses With Transformative Technologies (pp. 103-122). IGI Global.

Aliahmadi, A., Nozari, H., Ghahremani-Nahr, J., & Szmelter-Jarosz, A. (2022). Evaluation of key impression of resilient supply chain based on artificial intelligence of things (AIoT). arXiv preprint arXiv:2207.13174.

Aliahmadi, A., Sadeghi, M. E., Nozari, H., Jafari-Eskandari, M., & Najafi, S. E. (2015). Studying key factors to creating competitive advantage in science Park. In Proceedings of the ninth international conference on management science and engineering management (pp. 977-987). Springer Berlin Heidelberg.

Fallah, M., & Nozari, H. (2021). Neutrosophic mathematical programming for optimization of multi-objective sustainable biomass supply chain network design. Computer Modeling in Engineering & Sciences, 129(2), 927-951.

Fallah, M., Sadeghi, M. E., & Nozari, H. (2021). Quantitative analysis of the applied parts of Internet of Things technology in Iran: an opportunity for economic leapfrogging through technological development. Science and technology policy Letters, 11(4), 45-61.

Lotfi, F. H. Z., Najafi, S. E., & Nozari, H. (Eds.). (2016). Data envelopment analysis and effective performance assessment. IGI Global.

Mohammadi, H., Ghazanfari, M., Nozari, H., & Shafiezad, O. (2015). Combining the theory of constraints with system dynamics: A general model (case study of the subsidized milk industry). International journal of management science and engineering management, 10(2), 102-108.

Movahed, A. B., Movahed, A. B., & Nozari, H. (2024). Opportunities and Challenges of Smart Supply Chain in Industry 5.0. Information Logistics for Organizational Empowerment and Effective Supply Chain Management, 108-138.

Nozari, H., Tavakkoli-Moghaddam, R., & Gharemani-Nahr, J. (2022). A neutrosophic fuzzy programming method to solve a multi-depot vehicle routing model under uncertainty during the covid-19 pandemic. International Journal of Engineering, 35(2), 360-371.

Nozari, H., Tavakkoli-Moghaddam, R., Ghahremani-Nahr, J., & Najafi, E. (2023). A conceptual framework for Artificial Intelligence of Medical Things (AIoMT). In Computational Intelligence for Medical Internet of Things (MIoT) Applications (pp. 175-189). Academic Press.

Nozari, H., Tavakkoli-Moghaddam, R., Rohaninejad, M., & Hanzalek, Z. (2023, September). Artificial Intelligence of Things (AIoT) Strategies for a Smart Sustainable-Resilient Supply Chain. In IFIP International Conference on Advances in Production Management Systems (pp. 805-816). Cham: Springer Nature Switzerland.

Tavakkoli-Moghaddam, R., Ghahremani-Nahr, J., Samadi Parviznejad, P., Nozari, H., & Najafi, E. (2022). Application of internet of things in the food supply chain: a literature review. Journal of applied research on industrial engineering, 9(4), 475-492.

Published

2024-04-06

How to Cite

Bakhshi Movahed, A. (2024). Dimensions and main elements of data-driven agriculture. International Scientific Hub, 68–79. Retrieved from https://books.iscihub.com/index.php/ISCIHB/article/view/45

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