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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67624
Volume:
10 |
10 |
Oct 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of computer science
St. Joseph’s first grade college
Animal farming plays a significant role in the agricultural economy by providing employment, food security, and livelihood opportunities for rural communities. Despite its importance, animal farmers face several challenges, including limited awareness of government subsidies, difficulties in accessing agricultural loans, inappropriate breed selection, inefficient land utilization, financial losses due to animal mortality, and dependence on unorganized animal markets. These challenges often affect farm productivity, profitability, and sustainability. To address these issues, this paper proposes an AI-Based Farmer-Friendly Integrated Support Platform that provides comprehensive digital assistance to animal farmers through a unified system. The proposed platform integrates government scheme and subsidy discovery, loan eligibility assessment, land- and location-based farming recommendations, animal death compensation guidance, AI-based breed profitability prediction, a digital marketplace for buying and selling animals, and educational resources in text and video formats. Machine Learning and Deep Learning techniques are employed to analyze relevant agricultural, financial, environmental, and animal-related data for intelligent decision support. Predictive models are designed to estimate breed profitability, loan approval probability, and animal health/death risk, while recommendation mechanisms assist farmers in selecting suitable farming practices based on their available resources and location. The platform also provides links to official government portals to improve accessibility to welfare schemes and financial assistance. By integrating artificial intelligence with digital agricultural services, the proposed system aims to improve farmer decision-making, reduce information gaps and dependency on intermediaries, optimize resource utilization, and support more sustainable and profitable animal farming. The proposed framework demonstrates the potential of AI-driven AgriTech solutions to contribute to rural digital empowerment and improve access to essential services for animal farmers.
KEYWORDS
GoFarm demonstrates the effective use of Artificial Intelligence and Machine Learning to support livestock farmers. The system integrates subsidy information, loan assistance, breed selection, health-risk prediction, and livestock trading in one platform. AI-based models provide useful predictions and recommendations for better farming decisions. The platform reduces information gaps and dependency on middlemen while improving market accessibility. Overall, GoFarm can help improve productivity, profitability, decision-making, and sustainable livestock farming.
1] A. K. Mondal, S. S. Dhara, and S. K. Biswas: Management practices and perceived constraints in goat rearing by farmers, Indian Journal of Veterinary and Animal Sciences Research, vol. 45, no. 2, pp. 120–125, 2016. [2]N. Subbaiyan – Government Order on Compensation for Livestock Killed by Stray Dogs in Tamil Nadu – 2025 [3]Jasmine Isabella – Analysis of Government Subsidies on Livestock Farming Sustainability – 2023 [4]Rajalaxmi Behera, Adhikari Sahu, P.K Naik, D Kumar, B.K. Swain, S Dash, and S.K. Mishra (2026) - "Credit access and its impact on livestock farming in India"
Publication Date
10/2/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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