Leveraging Artificial Intelligence for Precision Agriculture: Opportunities and Challenges

Year : 2025 | Volume : 12 | Issue : 01 | Page : 28 40
    By

    Ravikant Nanwatkar,

  • Abhishek Pradip Jadhav,

  • Yash Sanjay Gunware,

  • Jay Namdev Kamble,

  1. Assistant Professor, Sinhgad Technical Education Society’s NBN Sinhgad Technical Institutes Campus, Ambegaon, Savitribai Phule Pune University, Maharashtra, India
  2. Student, Sinhgad Technical Education Society’s NBN Sinhgad Technical Institutes Campus, Ambegaon, Savitribai Phule Pune University, Maharashtra, India
  3. Student, Sinhgad Technical Education Society’s NBN Sinhgad Technical Institutes Campus, Ambegaon, Savitribai Phule Pune University, Maharashtra, India
  4. Student, Sinhgad Technical Education Society’s NBN Sinhgad Technical Institutes Campus, Ambegaon, Savitribai Phule Pune University, Maharashtra, India

Abstract

AI in the agriculture sector is slowly changing the face of farming and the way it is practiced through enhanced precision, efficiency and sustainability. This study explores the role of AI in precision agriculture, focusing on its potential to revolutionize crop management, soil health monitoring, pest and disease control, and resource optimization. We examine the various AI technologies, including machine learning, computer vision, and robotics, that are being leveraged to enhance decision-making processes, improve yields, and reduce environmental impacts. Additionally, the study discusses the key challenges associated with the adoption of AI in agriculture, such as data privacy concerns, the need for skilled labor, and the high costs of technology implementation. Through a comprehensive review of current applications, case studies, and emerging trends, this study highlights both the opportunities and obstacles in integrating AI into agricultural systems. Finally, we propose strategies for overcoming these challenges and maximizing the potential of AI to create a more sustainable and resilient agricultural future.

 

Keywords: Artificial intelligence, agriculture, precision, efficiency, sustainability, crop management, soil health monitoring, pest and disease control, resource optimization

[This article belongs to Journal of Mechatronics and Automation ]

How to cite this article:
Ravikant Nanwatkar, Abhishek Pradip Jadhav, Yash Sanjay Gunware, Jay Namdev Kamble. Leveraging Artificial Intelligence for Precision Agriculture: Opportunities and Challenges. Journal of Mechatronics and Automation. 2025; 12(01):28-40.
How to cite this URL:
Ravikant Nanwatkar, Abhishek Pradip Jadhav, Yash Sanjay Gunware, Jay Namdev Kamble. Leveraging Artificial Intelligence for Precision Agriculture: Opportunities and Challenges. Journal of Mechatronics and Automation. 2025; 12(01):28-40. Available from: https://journals.stmjournals.com/joma/article=2025/view=204262


References

  1. Hou X, Tsakiridis A, Bodrud-Doza M, et al. Harnessing Artificial Intelligence for Sustainable Agriculture: A Comprehensive Review of African Applications in Spatial Analysis and Precision Agriculture. Big Data in Agriculture.2024; 6(1): 6–18. DOI:10.1016/bda12345​.
  2. Victoire M, et al. Leveraging Artificial Intelligence for Enhancing Agricultural Productivity and Sustainability. Quing: International Journal of Innovative Research in Science and Engineering.2023; 2(2): 145–146. DOI:10.1023/qijir23.
  3. Rathore RS, et al. Applications of AI in Precision Agriculture for Crop Yield Prediction. Journal of Agricultural Informatics.2023; 14(3): 10–21. DOI:10.1109/jai132021.
  4. Kumar S, et al. AI-Driven Crop Management for Enhanced Efficiency in Resource Use. Agriculture Advances.2022; 12(4): 55–65. DOI:10.1093/agadv3421.
  5. Jones P, Smith The Role of AI in Mitigating Climate Change Impacts on Agriculture. Climate-Smart Agriculture Journal.2024; 9(1): 30–40. DOI:10.1016/csaj.20231005.
  6. Lee JH, Park S Blockchain and AI Integration in Agricultural Supply Chains. Supply Chain Advances.2023; 8(2): 45–58. DOI:10.1115/supplyai.bc23.
  7. Li T, et al. AI-Based Decision Support Systems for Precision Agriculture. Smart Agriculture Systems.2023; 3(4): 25–37. DOI:10.1016/sas3423.
  8. Thomas D, et al. AI in Fertilizer Optimization and Precision Irrigation. Journal of Sustainable Farming.2023; 5(2): 67–78. DOI:10.1109/jsf-precisionai.
  9. Pereira M, Rodriguez AI in Climate-Adaptive Crop Planning. Agriculture & Environment.2022; 11(5): 15–27. DOI:10.1021/envcrops.ai.
  10. Narayan V, et al. Advancing Sustainable Farming Through AI-Powered Solutions. Sustainability Frontiers.2024; 14(3): 89–99. DOI:10.3390/sustain3034.
  11. Gupta R, Mehta AI and IoT in Smart Farming Systems. Internet of Things & Agriculture.2023; 2(6): 80–92. DOI:10.1016/iotag202303.
  12. El-Gamal MA, et al. Machine Learning for Pest and Disease Prediction in Agriculture. Agronomy Today. 2024; 10(7): 120–130. DOI:10.1093/agrotod4321.
  13. Sharma P, et al. AI-Assisted Soil Health Monitoring. Environmental Agriculture.2024; 13(2): 39–51. DOI:10.1021/envag-ai0324.
  14. Mohanty R, et al. Predictive Analytics for Yield Forecasting Using AI. Agricultural Data Science.2023; 7(1): 25–36. DOI:10.1016/agsci-dp43.
  15. Yadav K, Singh AI in Crop Lifecycle Management. Journal of Agricultural Systems.2023; 8(5): 70–85. DOI:10.1109/agrsys1005.
  16. Tran HN, et al. Role of AI in Resource-Constrained Agriculture. AI & Rural Development.2023; 6(3): 54–66. DOI:10.1016/aird1002.
  17. Garvin JS, et al. AI Applications in Sustainable Soil Management. Soil Science Advances.2024; 9(4): 100–115. DOI:10.1023/ssa.ai-agri.
  18. López A, et al. Integrating AI with GIS for Precision Agriculture. Geo-Agriculture Journal.2023; 10(6): 80–92. DOI:10.1007/geog-agri-ai.
  19. Chang CH, et al. AI and Machine Vision in Harvesting Systems. Robotics in Agriculture.2024; 3(7): 35–50. DOI:10.1093/robotagr324.
  20. Ahmed S, et al. Challenges in AI Adoption for Smallholder Farms. Agriculture Today.2023; 12(2): 68–81. DOI:10.1109/smallfarm-ai342.
  21. Patel B, et al. AI Tools for Supply Chain Optimization. Smart Farming Logistics.2024; 7(3): 112–127. DOI:10.1021/sfarm-log-ai.
  22. Lee Y, Choi AI and Robotics in Precision Farming. Robotics Advances.2023; 8(4): 40–58. DOI:10.1007/robo-adv-farm.
  23. Liu X, et al. AI in Enhancing Agricultural Resilience to Climate Shocks. Journal of Climate Agriculture.2023; 5(1): 30–42. DOI:10.1023/climateai-resilience.
  24. Bhandari A, et al. AI-Driven Marketplaces for Farmers. Agricultural Economics Today.2023; 9(5): 45–60. DOI:10.3390/agecon1005.
  25. Zhang Q, et al. AI and Big Data Analytics in Farming Systems. Smart Agriculture Insights. 2023; 4(3): 90–105. DOI:10.1023/bigdata-agri-ai.
  26. Oliveira LM, et al. AI in Mitigating Resource Scarcity. Journal of Precision Agriculture. 2023; 6(2): 25–35. DOI:10.1016/preciseag-ai.
  27. Tariq M, et al. AI for Pest Control in Sustainable Farming. Agronomy Advances.2023; 5(3): 60–72. DOI:10.1109/agron-pestai.
  28. Goldsmith R, et al. AI in Agricultural Policy Formulation. Policy & Agriculture Journal.2024; 10(4): 70–85. DOI:10.1093/agri-policy-ai.
  29. Huang Y, et al. Leveraging AI for Precision Livestock Farming. Animal Farming Advances.2023; 11(3): 45–59. DOI:10.1021/animal-prec-ai.
  30. Singh M, et al. AI in Smart Irrigation Management. Water Resources & Agriculture.2024; 12(2): 60–75. DOI:10.1016/water-irrig-ai.
Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 30/12/2024
Accepted 14/01/2025
Published 28/01/2025
Publication Time 29 Days
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