FarmedIn: A Unified AI-Based Platform for Precision Agriculture Covering Crop Selection, Fertilizer Recommendation, and Disease Management

FarmedIn: A Unified AI-Based Platform for Precision Agriculture Covering Crop Selection, Fertilizer Recommendation, and Disease Management

Alisha Iddalagi, Saurabh Batwal, Ganesh Gaikwad, Soham Kabadi

Students of Datta Meghe College of Engineering, Airoli.

R.N. Mendhe
Datta Meghe College of Engg., Airoli-400708, Navi Mumbai,India

Abstract: Agriculture faces critical challenges due to soil degradation, climate variability, and inefficient resource management. Conventional farming techniques often lack data-driven decision-making, leading to suboptimal yields and excessive input usage. FarmedIn is an AI-powered smart farming system that integrates machine learning, real-time soil analysis, and climate data to optimize crop selection, fertilizer application, and plant health monitoring. The system employs deep learning models for disease detection, recurrent neural networks (RNNs) for crop and fertilizer recommendations, and a cloud-based web platform for accessibility. This research presents the architecture, methodology, and performance evaluation of FarmedIn, demonstrating its high accuracy in precision farming and its potential for large-scale agricultural transformation.

Keywords: Precision Agriculture, Machine Learning, Crop Disease Detection, Soil Health Monitoring, Smart Farming.