SMARTCROP : AGRICULTURE CROP RECOMMENDATION BASED ON FUTURE DEMAND
Alt Text: SMARTCROP: Agriculture Crop Recommendation Based on Future Demand Title: SMARTCROP: Agriculture Crop Recommendation Based on Future Demand Caption: A machine learning-based crop recommendation system designed to optimize agricultural productivity and market adaptability. Description: This study presents a predictive analytics-driven smart crop management system leveraging machine learning algorithms to analyze past data on crop yields, market trends, weather, and consumer preferences, ensuring well-informed decision-making for farmers. Keywords: Climate conditions, Market trends, Data analysis, Machine learning, Predictive analytics, Smart agriculture
International Journal of Engineering and Techniques – Volume 10 Issue 3, May 2024
Mrs. Amitha S1, Harshal V Pai2, Joshna M J3, Kavya S4, M Jeswanth5 1Associate Professor, Department of Computer Science and Engineering, K S School of Engineering and Management, Bangalore, Karnataka, India 2Student, Department of Computer Science and Engineering, K S School of Engineering and Management, Bangalore, Karnataka, India 3Student, Department of Computer Science and Engineering, K S School of Engineering and Management, Bangalore, Karnataka, India 4Student, Department of Computer Science and Engineering, K S School of Engineering and Management, Bangalore, Karnataka, India 5Student, Department of Computer Science and Engineering, K S School of Engineering and Management, Bangalore, Karnataka, India
Abstract
Using machine learning and predictive analytics to estimate future demand, this study introduces a novel crop management approach. Predictive models are generated based on past data covering crop yields, market trends, weather conditions, and consumer preferences. The system enhances agricultural decision-making by integrating climate analysis, soil health assessment, and dynamic market trends, promoting sustainability and optimized yields. Real-time data updates and feedback loops improve adaptability to shifting market dynamics, ensuring higher productivity and financial returns for farmers.
Mrs. Amitha S, Harshal V Pai, Joshna M J, Kavya S, M Jeswanth, “SMARTCROP: Agriculture Crop Recommendation Based on Future Demand,” International Journal of Engineering and Techniques, Volume 10, Issue 3, 2024. ISSN 2395-1303.
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