International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 01 | Jan 2025
p-ISSN: 2395-0072
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FarmTech: - Recommendation and Prediction System for Farmers Aayushi Maurya1, Kaniz Fatima Baig2, Nupur Bodke3, Dr. Dhananjay Theckedath4 1,2,3 Students of Thadomal Shahani Engineering College , Mumbai, Maharashtra , India.
Associate Professor of Thadomal Shahani Engineering College , Mumbai, Maharashtra , India. ---------------------------------------------------------------------***--------------------------------------------------------------------4
Abstract - In 2019, India witnessed over 10,000 farmer
These inefficiencies contribute to severe financial distress among farmers, leading to a tragically high number of farmer suicides. In 2019 alone, over 10,000 farmer suicides were reported, largely due to crop failures, mounting debts, and unpredictable weather conditions. At the core of these challenges is the lack of access to proper farming methods, advanced tools, and timely information, which continues to undermine the growth and sustainability of India’s agricultural landscape.
suicides, driven by crop failures, overwhelming financial burdens, and debt distress. These tragedies were exacerbated by unpredictable weather patterns, pest infestations, and market volatility, highlighting the vulnerabilities faced by farmers and the lack of access to modern agricultural technologies. To address these issues, we introduce FarmTech: Prediction and Recommendation System for Farmers, a versatile platform designed for farmers through data-driven insights. The platform offers a Fertilizer Recommendation System, which provides optimized solutions to enhance soil health and reduce chemical overuse. The Crop Recommendation System helps farmers select the most suitable crops based on soil conditions and climate. Additionally, FarmTech integrates a Plant Disease Recognition System, employing image processing and machine learning to diagnose crop diseases and enable timely interventions quickly. To further enhance usability, an Interactive Chatbot is included to offer real-time advice and address farmer queries. By leveraging AI-driven technologies and realtime agricultural data, FarmTec aims to tackle the challenges of modern farming, promote sustainable practices, and provide farmers with the tools needed to navigate economic, environmental, and technological hurdles.
Machine learning (ML) is transformative in shaping various aspects of our lives, from enhancing everyday conveniences to driving innovation in multiple industries. Its ability to process vast amounts of data, recognize patterns, and make intelligent predictions has led to transformative changes in sectors such as healthcare, finance, transportation, and entertainment. Across industries, ML is a crucial tool for improving efficiency, personalizing experiences, and driving breakthroughs. When it comes to agriculture, machine learning has the potential to radically transform farming practices, helping to address many of the challenges faced by farmers today. Agriculture is a data-rich field where decisions about soil management, crop selection, pest control, irrigation, and yield prediction can all benefit from data-driven insights. Our project aims to address all these issues with FarmTech: Prediction and Recommendation System for Farmers, a platform designed to revolutionize farming practices in India by offering data-driven insights and AIpowered tools. FarmTech integrates a Fertilizer Recommendation System, which provides tailored advice based on soil health to ensure optimal nutrient use, enhancing crop growth and preserving soil quality. The Crop Recommendation System suggests the most suitable crops based on soil composition, climate conditions, and market trends, helping farmers make informed decisions that increase yield potential.
Key Words: Prediction, Recommendation, soil health, Plant Disease, AI-driven, sustainable, Fertilizer
1. INTRODUCTION India's economy, which is among the fastest-growing in the world and is currently the fifth largest in terms of nominal GDP, is confronted with considerable obstacles in the agricultural sector. More than 50% of India's workforce is employed in agriculture, which generates 16– 17% of the nation's GDP and is mostly dependent on traditional practices. This reliance on primitive methods hinders production and restricts overall economic progress, especially when combined with restricted access to innovative, effective farming technology. As a result, the industry deals with problems like low crop yields, inefficient resource use, and unsustainable farming methods, which strain rural livelihoods and have a wider impact on the national economy, limiting the potential of an industry essential to India's food security and economic stability.
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Additionally, FarmTech includes a Plant Disease Recognition System, leveraging image processing and machine learning to quickly diagnose crop diseases and recommend treatments. To further support farmers, an Interactive Chatbot is available for real-time query resolution, offering instant advice on various agricultural practices.
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