The Impact of Kisan Call Centers on the Farming Sector

Chachra, Kartik; Seelam, Gowtham; Singh, Harshinder; Sarkar, Mayukh; Jain, Anshul; Jain, Ankush

doi:10.4018/978-1-5225-9621-9.ch004

Cited by 4 publications

(2 citation statements)

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“…In 2004, the Indian government started a program to provide telephonic help to the countrywide farmers in their local language on the toll-free number "1800-180-1551". Moreover, many studies have shown the program's positive outcomes in farmers' livelihood and economic conditions over the years ( [3], [4], [5]).…”

Section: Introductionmentioning

confidence: 99%

AgriResponse: A Real-Time Agricultural Query-Response Generation System for Assisting Nationwide Farmers

Godara,

Bedi,

Parsad

et al. 2024

IEEE Access

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Advancements in information sciences can play a vital role in strengthening the nation's sustainable agriculture goals. In this direction, we propose a framework for a text-based query-response generation system to cope with the demand for timely help to the nationwide Indian farmers. One of the major challenges in designing such systems is constructing a knowledge base that can answer plantprotection-related questions from a diverse population of farmers. To tackle this problem, the past eight years' call-log records from the countrywide farmers' helpline network are collected and processed to construct the required knowledge base. Additionally, three response-retrieval models with approximate matching and spatial-based searching functionality are developed to administer the user input questions and extract relevant answers from the base. To validate the performance of the proposed framework, a diversified question bank consisting of 755 queries covering 151 crops in India is compiled. Three metrics (Accuracy Percentage, Crop-weighted Performance Score, and Average Response-retrieval time) are considered for the models' assessment. Experimental results show that AgriResponse is a practical framework in real-world applications, with the different retrieval models useful for different scenarios.

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Section: Introductionmentioning

confidence: 99%

AgriResponse: A Real-Time Agricultural Query-Response Generation System for Assisting Nationwide Farmers

Godara,

Bedi,

Parsad

et al. 2024

IEEE Access

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“…Over the years, it has become a cornerstone of agricultural assistance, offering farmers a platform to seek guidance, information, and solutions to their pressing agricultural concerns (Godara & Toshniwal, 2020;. The KCC, operated by the Punjab government, records and manages an extensive dataset of farmer query calls, encompassing various topics, from crop cultivation techniques to pest management strategies and government schemes (Chachra et al 2020; Kaur et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Decoding agricultural needs: An in-depth analysis of farmer queries in Punjab's Kisan call center

Godara,

Bana,

Godara

et al. 2023

J. Agric. Ecol.

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Adopting a demand-driven approach in a rapidly changing agricultural sector is crucial for extension services to remain relevant and impactful in India. In this direction, the article presents a comprehensive analysis of over two million farmer query calls made to the Kisan Call Center in Punjab, India, from January 2009 to August 2023. These preprocessed call logs are a vital link between farmers and agricultural support services, providing valuable insights into the agricultural community's challenges and requirements. Our analysis commences by examining temporal trends in farmer query calls, offering year-wise statistics that unveil the evolution of call volumes over time. Furthermore, we delve into the dataset to provide month-wise insights, shedding light on the seasonality of these queries. By identifying peak months of call activity, we can pinpoint critical periods when farmers require assistance the most. Furthermore, district-wise analysis aids in mapping the geographical distribution of these calls, enabling policymakers and agricultural authorities to target specific regions with tailored interventions. Our breakdown by crop category and query type also provides a granular perspective on farmers' concerns. By categorising calls based on the crops and query types, we gain valuable insights into the distinct challenges faced by Punjab's farmers. This information can guide the development of agricultural policies, extension services, and support programs tailored to address the unique needs of different crop categories and query types. Ultimately, this study underscores the significance of harnessing data-driven insights to enhance agricultural support systems, ensuring India's farming community's long-term sustainability and prosperity.

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Deep Learning-based query-count forecasting using farmers’ helpline data

Godara

Toshniwal

2022

Computers and Electronics in Agriculture

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The Impact of Kisan Call Centers on the Farming Sector

Cited by 4 publications

References 0 publications

AgriResponse: A Real-Time Agricultural Query-Response Generation System for Assisting Nationwide Farmers

AgriResponse: A Real-Time Agricultural Query-Response Generation System for Assisting Nationwide Farmers

Decoding agricultural needs: An in-depth analysis of farmer queries in Punjab's Kisan call center

Deep Learning-based query-count forecasting using farmers’ helpline data

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