Authors :
Oluwakemi Temitope Olayinka
Volume/Issue :
Volume 10 - 2025, Issue 3 - March
Google Scholar :
https://tinyurl.com/2xvz59eu
Scribd :
https://tinyurl.com/2hct6ars
DOI :
https://doi.org/10.38124/ijisrt/25mar1819
Google Scholar
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Abstract :
Agriculture is undergoing a radical transformation driven by technological innovations, particularly the Internet
of Things (IoT), Artificial Intelligence (AI), and Advanced Analytics (AA). These technologies promise to improve resource
management, increase crop yields, and optimize supply chains. IoT enables real-time data collection through interconnected
devices like sensors and drones, while AI processes this data for informed decision-making on irrigation, fertilization, and
pest control. Advanced Analytics further enhances precision farming by predicting trends and improving operational
efficiency. Drawing insights from sectors such as healthcare, manufacturing, and transportation, this article highlights how
these technologies are revolutionizing agriculture. It also explores future trends like autonomous machinery and AI-driven
crop management models, underscoring the potential of IoT, AI, and AA to boost sustainability, productivity, and
profitability in the agricultural sector.
References :
- Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. X. (2017). A review on the practice of big data analysis in agriculture. *Computers and Electronics in Agriculture, 143*, 23–37. https://doi.org/10.1016/j.compag.2017.09.037
- Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. *Sensors, 18*(8), 2674. https://doi.org/10.3390/s18082674
- Ray, D. K., Mueller, N. D., West, P. C., & Foley, J. A. (2013). Yield trends are insufficient to double global crop production by 2050. *PLoS ONE, 8*(6), e66428. https://doi.org/10.1371/journal.pone.0066428
- Rose, D. C., Wheeler, R., Winter, M., Lobley, M., & Chivers, C. A. (2016). Agricultural stakeholders' perceptions of the effectiveness and usefulness of digital tools in managing agricultural risks. *Agricultural Systems, 149*, 165–174. https://doi.org/10.1016/j.agsy.2016.07.009
- Verdouw, C., Wolfert, S., Beulens, A. J. M., & Rialland, A. (2016). Virtualization of food supply chains with the internet of things. *Journal of Food Engineering, 176*, 128–136. https://doi.org/10.1016/j.jfoodeng.2015.11.009
- Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M.-J. (2017). Big data in smart farming – A review. *Agricultural Systems, 153*, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023
- Zhang, Y., Wang, G., Wang, J., & Wang, J. (2022). Review of precision agriculture and IoT applications in crop management. *Journal of Cleaner Production, 339*, 130718. https://doi.org/10.1016/j.jclepro.2022.130718
- Oluwakemi Temitope Olayinka is a product manager, tech writer, and researcher with a passion for using digital technologies to solve real-world challenges in agriculture, logistics, and emerging markets. She is currently exploring the intersection of IoT, AI, and data science in sustainable farming.
- “The Digital Farmer: How AI is Changing Agriculture”
- “AgriTech Startups to Watch in 2025”
- “Data Privacy and Ethics in Smart Farming Systems”
Agriculture is undergoing a radical transformation driven by technological innovations, particularly the Internet
of Things (IoT), Artificial Intelligence (AI), and Advanced Analytics (AA). These technologies promise to improve resource
management, increase crop yields, and optimize supply chains. IoT enables real-time data collection through interconnected
devices like sensors and drones, while AI processes this data for informed decision-making on irrigation, fertilization, and
pest control. Advanced Analytics further enhances precision farming by predicting trends and improving operational
efficiency. Drawing insights from sectors such as healthcare, manufacturing, and transportation, this article highlights how
these technologies are revolutionizing agriculture. It also explores future trends like autonomous machinery and AI-driven
crop management models, underscoring the potential of IoT, AI, and AA to boost sustainability, productivity, and
profitability in the agricultural sector.