Improvement of Agriculture Productivity by using Artificial Intelligence and Block Chain Technology

Authors

  • Anusuri Krishna Veni  Assistant Professor, Department of Data Science, Madanapalle institute of Technology & Science, Andhra Pradesh, India
  • K Shwetha Rani  Assistant Professor, CSE Department, TKR College of Engineering and Technology, Hyderabad, India

DOI:

https://doi.org/10.32628/IJSRST52310451

Keywords:

precision agriculture; supply chain; blockchain; internet of things; traceability; smart contracts

Abstract

Agriculture plays a vital role in global food security and economic sustainability. However, the sector faces numerous challenges, such as the need to feed a growing population, resource constraints, climate change, and inefficient supply chain management. This paper explores the potential of integrating Artificial Intelligence (AI) and Blockchain technology to address these challenges and boost agricultural productivity. AI can revolutionize decision-making and data analysis, while Blockchain offers transparency, traceability, and security. By synergizing these technologies, agriculture can transition towards a more efficient, sustainable, and resilient future.

References

  1. G. S. Nagaraja, A. B. Soppimath, T. Soumya and A. Abhinith, "IoT based smart agriculture management system", Proc. 4th Int. Conf. Comput. Syst. Inf. Technol. Sustain. Solution (CSITSS), pp. 1-5, Dec. 2019.
  2. E. Siddhartha and M. C. Lakkannavar, "Smart irrigation and crop health prediction", Proc. Int. Conf. Recent Trends Electron. Inf. Commun. Technol. (RTEICT), pp. 739-742, Aug. 2021.
  3. United Nation Global Population Growth and Sustainable Development, Apr. 2022, [online] Available: https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/ undesa_pd_2022_global_population_growth.pdf.
  4. K. Parasuraman, U. Anandan and A. Anbarasan, "IoT based smart agriculture automation in artificial intelligence", Proc. 3rd Int. Conf. Intell. Commun. Technol. Virtual Mobile Netw. (ICICV),
  5. J. Treboux and D. Genoud, "Improved machine learning methodology for high precision agriculture", Proc. Global Internet Things Summit (GIoTS), pp. 1-6, Jun. 2018.
  6. R. Alfred, J. H. Obit, C. P.-Y. Chin, H. Haviluddin and Y. Lim, "Towards paddy Rice smart farming: A review on big data machine learning and Rice production tasks", IEEE Access, vol. 9, pp. 50358-50380, 2021.
  7. Sharma, A. Jain, P. Gupta and V. Chowdary, "Machine learning applications for precision agriculture: A comprehensive review", IEEE Access, vol. 9, pp. 4843-4873, 2021.
  8. F. Kiani and A. Seyyedabbasi, "Wireless sensor network and Internet of Things in precision agriculture", Int. J. Adv. Comput. Sci. Appl., vol. 9, no. 6, pp. 1-5, 2018.
  9. O. Elijah, T. A. Rahman, I. Orikumhi, C. Y. Leow and M. N. Hindia, "An overview of Internet of Things (IoT) and data analytics in agriculture: Benefits and challenges", IEEE Internet Things J., vol. 5, no. 5, pp. 3758-3773, Oct. 2018.
  10. E. Alreshidi, "Smart sustainable agriculture (SSA) solution underpinned by Internet of Things (IoT) and artificial intelligence (AI)", Int. J. Adv. Comput. Sci. Appl., vol. 10, no. 5, pp. 93-102, 2019.
  11. Mat, M. R. M. Kassim, A. N. Harun and I. M. Yusoff, "IoT in precision agriculture applications using wireless moisture sensor network", Proc. IEEE Conf. Open Syst. (ICOS), pp. 24-29, Oct. 2016.

International Journal of Scientific Research in Science and Technology

Downloads

Published

2023-08-30

Issue

Volume 10, Issue 4, July-August-2023

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Anusuri Krishna Veni, K Shwetha Rani "Improvement of Agriculture Productivity by using Artificial Intelligence and Block Chain Technology" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 10, Issue 4, pp.445-456, July-August-2023. Available at doi : https://doi.org/10.32628/IJSRST52310451