AI-Driven Agriculture with IoT Soil Analysis, Fertilizer Recommendations, and Local Marketplace for Sustainable Farming
Year: 2025
Type: article
Abstract: The agriculture sector is undergoing a technological transformation to address rising concerns around soil degradation, resource inefficiency, and limited market access for farmers.This paper presents a comprehensive smart farming system that integrates IoT-enabled soil analysis, AI-based fertilizer recommendations, and a mobile marketplace, empowering farmers with data-driven decision-making and direct access to buyers.The system combines real-time data collection through a 7-in-1 soil sensor with a trained machine learning model that predicts optimal organic and inorganic fertilizers and their application quantities based on soil, crop, and climatic parameters.An Android app, built using Kotlin Jetpack Compose, serves as the user interface for farmers, offering step-by-step soil testing guidance, government scheme updates, nutrient plans, pest alerts, and a local produce marketplace.The solution promotes sustainable agriculture, improves crop productivity, and enhances farmer profitability.This paper also discusses the system's design architecture, machine learning methodology, sensor integration, and expected field performance.Results indicate the platform's potential to revolutionize precision farming in regions with limited access to agronomic expertise.
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4413883013