Agriculture Optimization System |
Author(s): |
| Mohd Firoz Quraishi , Raj Kumar Goel Institute Of Technology; Mohd Firoz Quraishi, Raj Kumar Goel Institute Of Technology; Mohd Taufeek Ansari, Raj Kumar Goel Institute Of Technology; Swapnil Singh, Raj Kumar Goel Institute Of Technology; Ms. Vaishali Rastogi, Raj Kumar Goel Institute Of Technology |
Keywords: |
| Precision Agriculture, Machine Learning, Crop Yield Prediction, IoT in Agriculture, Smart Farming, Resource Management, Data-driven Agriculture, Sustainable Agriculture |
Abstract |
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Agriculture optimization system is transforming the agricultural sector by boosting productivity, optimizing input usage, and reducing ecological footprints. This study introduces a holistic framework that leverages machine learning methodologies for forecasting crop yields and managing agricultural resources, with the goal of enhancing decision-making in farming practices. We investigate several machine learning approaches, such as regression models and deep learning networks, to estimate crop outputs using historical records, soil properties, and climatic data. Additionally, we present an adaptive resource distribution mechanism that efficiently allocates water, fertilizers, and other inputs based on yield projections and real-time field information. The outcomes reveal notable improvements in prediction accuracy and resource utilization, offering a strong pathway toward environmentally friendly and data-driven agriculture. |
Other Details |
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Paper ID: IJSRDV13I30111 Published in: Volume : 13, Issue : 3 Publication Date: 01/06/2025 Page(s): 120-126 |
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