Comparative Analysis of Machine Learning Models for Optimizing Sustainable Agriculture and Farmer Profitability
Year: 2024
Type: article
Abstract: This paper presents a revolutionary AI-based platform designed to transform agricultural practices through data-driven decision-making. By addressing critical issues such as land underutilization, crop selection challenges, market volatility, and limited technological access, the platform provides actionable insights that enhance productivity and sustainability. It integrates advanced machine learning algorithms and features multilingual AI voice assistants to improve user convenience across diverse farming communities. The functionalities of the platform are examined, with a focus on its innovative tools tailored specifically for farmers. Ultimately, this research highlights the platform's potential to enhance agricultural efficiency, promote economic resilience among farmers, and contribute to the development of a more sustainable agricultural future.
Author: Prachi Janrao
Institution: Thakur College of Engineering and Technology
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4407042941