A Review: Farm Fusion AI for Agriculture

Authors

  • Ramakant Govind Chaudhari G H Raisoni College of Engineering and Management, Jalgaon, India
  • Ritesh Sheshrao Chaudhari G H Raisoni College of Engineering and Management, Jalgaon, India
  • Revati Shyam Pagare G H Raisoni College of Engineering and Management, Jalgaon, India
  • Tushar Ravindra Tambatkar G H Raisoni College of Engineering and Management, Jalgaon, India

Keywords:

Smart Agriculture,Precision Agriculture, Smart Farming, Agricultural Data Analytics, Crop Monitoring, Crop Disease Detection, Pest Detection,Crop Selection

Abstract

Agriculture is one of the most important sectors for global food security, yet farmers face numerous challenges such as unpredictable weather, crop diseases, pest attacks, soil degradation, and inefficient resource management. Farm Fusion AI for Agriculture is an AI-powered smart farming platform that integrates Artificial Intelligence (AI), Machine Learning (ML), the Internet of Things (IoT), and data analytics to improve agricultural productivity and support informed decision-making. The platform provides end-to-end assistance throughout the entire crop lifecycle, including land preparation, crop selection, sowing, irrigation, fertilizer management, weed control, disease and pest detection, crop monitoring, harvesting, and yield prediction. The proposed system utilizes AI and ML algorithms to analyze agricultural data, including soil properties, weather forecasts, crop health, and satellite or IoT sensor data, to generate intelligent recommendations at every stage of farming. Predictive analytics enable farmers to determine the optimal sowing time, optimize irrigation schedules, recommend suitable fertilizers, detect crop diseases and pest infestations at an early stage, and estimate crop yield before harvest. By providing real-time, data-driven insights, Farm Fusion AI enhances productivity, reduces resource wastage and production  costs,  and promotes  sustainable precision agriculture. The proposed solution empowers farmers with intelligent decision-support tools, leading to improved crop yield,

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Published

2026-10-01