Data-Driven Insights: A Critical Analysis of Farmer Call Centre Data Using Machine Learning Techniques
DOI:
https://doi.org/10.22399/ijcesen.1348Keywords:
Kishan Call Center, Machine Learning algorithms, Natural Language Processing, Query Processing, VisualizationAbstract
The agricultural sector plays a crucial role in India's economy, society, and environment. Agriculture is the primary source of livelihood for a significant portion of the Indian population, employing over half of the country's workforce. It contributes substantially to the Gross Domestic Product (GDP) and remains a vital sector for rural development and poverty alleviation. Experts use different kinds of smart systems to figure out problems on farms and find possible solutions. The systems help the experts collect and analyze information regarding the issues farmers meet. This study aimed to investigate the query data from Kisan Call Centers (KCCs) from 2020 to 2023 to identify key issues, understand farmers' challenges, and provide data-driven policy and program development insights. Python was used for data processing, Power BI for visualization, and Machine learning algorithms and Natural Language Processing libraries for query analysis
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