American Journal of Advanced Multidisciplinary Research and Innovation

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The Role of Artificial Intelligence in Precision Agriculture: A Sustainable Farming Perspective

Author(s) Dina Katabi
Country United States
Abstract The global agricultural sector faces increasing challenges due to climate change, population growth, declining natural resources, soil degradation, water scarcity, and the need for sustainable food production. Precision agriculture has emerged as an innovative approach that integrates advanced digital technologies to optimise agricultural practices, improve productivity, and minimise environmental impact. Artificial Intelligence (AI) has become a transformative technology within precision agriculture by enabling data-driven decision-making, predictive analytics, intelligent automation, and resource optimisation. Through the integration of Machine Learning (ML), Deep Learning, Internet of Things (IoT), remote sensing, drones, robotics, satellite imagery, Geographic Information Systems (GIS), and smart farming platforms, AI enables farmers to monitor crop health, predict yields, detect diseases, optimise irrigation, and manage agricultural resources efficiently.
This study investigates the role of Artificial Intelligence in precision agriculture from a sustainable farming perspective using a qualitative and analytical research methodology based on secondary data collected from scientific literature, agricultural technology reports, international organisations, and multidisciplinary case studies. The study examines AI applications in crop monitoring, soil analysis, pest and disease detection, climate-smart farming, autonomous machinery, livestock management, supply chain optimisation, and sustainable resource management. Furthermore, it evaluates the integration of AI with IoT, edge computing, blockchain, digital twins, and predictive modelling for developing intelligent agricultural ecosystems.
The findings indicate that AI significantly improves agricultural productivity, resource efficiency, environmental sustainability, and farmer decision-making. AI-enabled precision agriculture reduces water consumption, decreases chemical inputs, enhances crop quality, improves yield prediction accuracy, and supports climate-resilient farming practices. However, challenges including high implementation costs, limited digital infrastructure, data privacy concerns, technological literacy gaps, algorithmic bias, and accessibility issues remain significant barriers, particularly for small-scale farmers.
The study concludes that Artificial Intelligence provides a comprehensive framework for sustainable agricultural transformation by enabling intelligent, efficient, and environmentally responsible farming systems. Future agricultural development requires collaboration among farmers, researchers, policymakers, technology providers, and agricultural institutions to ensure inclusive and ethical adoption of AI-driven precision farming technologies.
Keywords Artificial Intelligence, Precision Agriculture, Sustainable Farming, Machine Learning, Internet of Things, Smart Farming, Crop Monitoring, Agricultural Automation, Climate-Smart Agriculture.
Field Engineering
Published In Volume 1, Issue 2, March-April 2019
Published On 2019-04-22
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