ROLE OF ARTIFICIAL INTELLIGENCE IN FARMING-A CASE STUDY

Authors

  • T Giri Babu Associate Professor, Dept of CSE, G.Pullaiah college of Engineering & Technology, Kurnool, Andhra Pradesh, India Author
  • P. Swathi Academic Consultant, Dept of computer science, SVU CM CS, India Author
  • P Jyotsna Academic consultant, Dept of computer science, SVU CM CS, India Author

Keywords:

Agriculture, Economic Sector, Population Growth, Automation Methods, Artificial Intelligence, Crop Production, Real-time Monitoring, Harvesting, Processing, Marketing, Climate Change, Employment, Food Safety, Technology-based Systems, Weeds Detection, Yield Prediction, Crop Quality Estimation

Abstract

Agriculture plays a major role in the economic sector for our country. The world`s population also increases day by day, and so the demand for food increasing rapidly. The general methods that are used in the farming are not sufficient to meet the needs of the increased population. Hence, some of the new automation methods are using to meet these requirements and to provide better job opportunities to more number of people in the agriculture sector. At present, Artificial Intelligence has become the most prominent technologies in agriculture sector. It is playing a very crucial role, and it is transforming the agriculture industry future. In fact, AI is trying to save the agriculture sector from different issues such as climate change, population growth, employment issues in this field, and support food safety. Artificial Intelligence helps to enhance crop production and real-time monitoring of filed, harvesting the crop, processing the crop and marketing also. Different high end technology based computer systems are introduced to find various parameters such as weeds detection, yield prediction, crop quality estimation, and many more other parameters.

References

"Applications of Artificial Intelligence in Agriculture: A Review" by Kavita Sharma et al. (International Journal of Computer Applications, 2017): Provides an overview of AI techniques and their applications in various aspects of agriculture.

"Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art" by Devis Tuia et al. (IEEE Geoscience and Remote Sensing Magazine, 2018): Discusses the application of deep learning techniques to analyse remote sensing data for agricultural monitoring.

"Machine Learning in Agriculture: A Review" by S. Pradhan et al. (International Journal of Computer Applications, 2019): Reviews the application of machine learning techniques in agriculture, including crop monitoring, yield prediction, and disease detection.

"A Review on Deep Learning Techniques Applied to Agricultural Problems" by Agustinus Kristiadi and Yuichi Motai (Computers and Electronics in Agriculture, 2020): Provides a comprehensive review of deep learning techniques and their applications in various agricultural tasks.

"AI in Agriculture: A Comprehensive Review" edited by Arun K. Nandi et al. (CRC Press, 2021): Offers a comprehensive overview of AI applications in different areas of agriculture, including crop monitoring, pest management, and farm automation.

"Precision Agriculture Technology for Crop Farming" by Rolf Gebbers and Kazumasa Wakita (CRC Press, 2015): Discusses the use of advanced technologies, including AI, GIS, and remote sensing, for precision agriculture practices.

"Artificial Intelligence in Agriculture" by Pravin D. Potdar and Atul M. Gajare (Apple Academic Press, 2022): Provides insights into the application of AI techniques such as machine learning, deep learning, and robotics in agriculture, along with case studies and future directions.

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Published

2024-03-23

How to Cite

T Giri Babu, P. Swathi, & P Jyotsna. (2024). ROLE OF ARTIFICIAL INTELLIGENCE IN FARMING-A CASE STUDY. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY (IJCET), 15(2), 17-24. https://mylib.in/index.php/IJCET/article/view/IJCET_15_02_004