Plant and Soil Health Analyzer: An AI-Driven Web- Based Agricultural Decision Support System

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Authors: Balakrishna D. R, Safura Mariyam, Sanjana JK, Shafiya Muskaan, Vidyashree M
Cited by: 0

Abstract

Agriculture keeps feeding the world, but today’s farms face tougher soils, uneven nutrients, patchy care, and also spreading crop illnesses. Old ways of checking soil or plants rely on labs, chemicals, even specialists - costing too much, taking too long, and leaving out smaller growers. At the same time, missing live updates means spotting sickness late, which often slashes harvests. Now, thanks to smart algorithms, neural networks, plus visual recognition tech, cheap photo-driven tools can help fix these gaps fast. This study introduces Green Thumb - a smart tool running online that checks plant health and soil quality through phone pictures alone. Instead of needing lab tests, it spots crop diseases, judges how green the farm is, guesses nutrients in dirt, plus plans upkeep tasks on its own. Built with Next.js up front and powered by FastAPI behind the scenes, it runs CNNs, uses Mobile Net to pull image details, along with math models for guessing mineral levels. Rather than relying on single methods, it mixes feature pulls from different sources, gives live answers, and shows data clearly through charts you can click around. Tests show it nails pH and NPK estimates, sorts sick plants right most times, works well across crops like corn, tomatoes, or beans. Real growers tried it out, said they liked using it, found it helpful without being tricky. So this isn't just another flashy app; it's built cheap, scales easily, helps small farms stay sharp where tools and cash are tight.

Fields of Study & Subjects

Smart Agriculture and AI Smart Systems and Machine Learning Internet of Things and AI

Publication details

Journal / source
International Journal Of Recent Trends In Multidisciplinary Research
Pages
212–218
Publication date
2 January 2026