Artificial Intelligence (AI) Based Smart Agriculture for Sustainable Development

Authors

  • Gurwinder Kaur Department of Food Science and Technology, I .K. Gujral Punjab Technical University, Kapurthala
  • Barinderjit Singh Department of Food Science and Technology, I .K. Gujral Punjab Technical University, Kapurthala
  • Anil Kumar Angrish Department of Pharmaceutical Management, National Institute of Pharmaceutical Education and Research, Mohali
  • Sanjeev K. Bansal Department of Management, I .K. Gujral Punjab Technical University, Kapurthala

DOI:

https://doi.org/10.33516/maj.v57i6.54-57p

Keywords:

No Keywords.

Abstract

Agriculture plays a significant role in the economic growth and development. Over the years, AI-based technological improvements have profoundly impacted farming and transformed the business. These technologies could help farmers to be proactive rather than reactive in their farming practices. These technologies allow farmers to boost agricultural yield, soil analysis, pest attack monitoring, water management, seed management, crop rotation, better control of harvesting conditions and timing, nutrition management, and reduced waste. However, in order to reap all these benefits, effective collaboration between Government, science, and business is also vital. This article attempts to outline the significant AI based smart agricultural technologies, their significance and the challenges confronting Indian agriculture with potential solutions.

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Published

2022-06-30

How to Cite

Kaur, G., Singh, B., Angrish, A. K., & Bansal, S. K. (2022). Artificial Intelligence (AI) Based Smart Agriculture for Sustainable Development. The Management Accountant Journal, 57(6), 54–57. https://doi.org/10.33516/maj.v57i6.54-57p

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Cover Story

References

https://www.fao.org/3/i6583e/i6583e.pdf (accessed on Apr.19, 2022)

https://www.marketwatch.com/press-release/artificial-intelligence-ai-market-leading-growth-drivers-emerging-audience-segments-industry-sales-profits-and-forecast-2022-2031-2022-03-21(accessed on Apr.19, 2022).

https://indianexpress.com/article/india/agriculture-ministry-inks-mou-with-5-firms-7509545/ (accessed on Apr.19, 2022).

Dharmaraj, V. and Vijayanand, C. (20180. Artificial Intelligence (AI) in Agriculture. International Journal of Current Microbiology and Applied Sciences 7(12): 2122-2128.

Royston, R. M. and Pavithra, M.P. (2018). Vertical Faming: A Concept. International Journal of Engineering and Techniques. 4 (3): 500-506.

Kavga, A.; Bitas, D.; Papastavros, K.; Prapopoulos, M. and Kotsiris, G. (2021). Development of an Integrated IoT-based Greenhouse Control Cablebot System. Information and Communication Technologies in Agriculture, Food & Agriculture. 2761: 518-525.

Vibhute, A. and Bodhe, S. K. (2012). Applications of Image Processing in Agriculture: A Survey. International Journal of Computer Applications. 52 (2):34-40.

Kulkarni, A. A.; Dhanush, P.; Chetan, B. S.; Thamme Gowda, C. S. and Shrivastava, P. K. (2002). Applications of Automation and Robotics in Agriculture Industries: A Review. International Conference on Mechanical and Energy Technologies.748:1-7.

Misra, N. N.; Dixit, Y.; Al-Mallahi, A.; Bhullar, M. S.; Upadhyay, R. and Martynenko, A. (2020). IoT, big data and artificial intelligence in agriculture and food industry. IEEE Internet of Things Journal. 1(1): 6305 - 6324.

https://economictimes.indiatimes.com/news/economy/agriculture/who-will-pay-for-the-kisandrone/articleshow/89530562. cms?from=mdr (accessed on Apr.29, 2022).

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