Controlling Food Security AI IoT is a B.Tech project topic for Agricultural Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Controlling Food Security AI IoT Project Details
| Abstract |
This study addresses critical concerns arising from food scarcity, particularly focusing on the needs of low-income farmers in rural, resource-constrained environments characterized by eminent climate unpredictability. It proposes an integrated framework leveraging Artificial Intelligence (AI) and the Internet of Things (IoT) to establish intensified, enhanced, and navigable smart agricultural practices, specifically aimed at guaranteeing food security. The methodology involves the integration of IoT for real-time data acquisition and weather forecasting, which is utilized to optimize rainfall management, improve soil fertility, and enhance crop yielding mechanisms, offering a significant advancement over conventional farming techniques. A Machine Learning (ML) component is incorporated to strengthen the system's knowledge base and empower farmers with
accurate decision-making capabilities, precision agriculture insights, and robust evaluation and impact assessment tools throughout the agricultural cycle. The framework prioritizes a participatory implementation approach to ensure affordability, usability, and data accessibility, facilitating a comparative analysis between enhanced and traditional farming methodologies based on data collection, practical implementation, and user experience. This comprehensive strategy aims to provide sustainable solutions for agricultural productivity and food security.
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| Reference Paper |
Controlling Food Security with AI and IoT for Smart Farming Among Low-Income Earners |
| Domain |
Agricultural Engineering |
| Sub-Domain |
Agricultural Engineering |
| PDF Download |
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| Get Help |
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