Artificial Intelligence in Sustainable Agriculture: Integrating Precision Farming, Predictive Analytics and IoT

Diane Burton

Artificial Intelligence in Sustainable Agriculture: Integrating Precision Farming, Predictive Analytics and IoT

Author(s)	Diane Burton
Country	United States
Abstract	Agriculture is increasingly challenged by climate variability, water scarcity, soil degradation, rising production costs, population growth, and the need to produce more food while reducing environmental impacts. The integration of Artificial Intelligence (AI), precision farming, predictive analytics, and the Internet of Things (IoT) offers new opportunities to address these challenges. AI-enabled agricultural systems can process data from sensors, satellites, drones, weather stations, machinery, and farm-management platforms to support real-time decision-making and optimize the use of agricultural resources. This study examines how the integration of AI, precision farming, predictive analytics, and IoT can contribute to sustainable agricultural production. A qualitative and conceptual research methodology based on academic literature and agricultural technology research is adopted. The study examines applications in soil management, irrigation, crop monitoring, disease detection, yield prediction, pest management, and agricultural supply chains. The analysis indicates that integrated AI-IoT systems can improve resource-use efficiency, reduce unnecessary input consumption, support early disease detection, and improve farm productivity. However, challenges related to connectivity, data quality, technology costs, farmer skills, interoperability, cybersecurity, and unequal access may limit adoption, particularly among smallholder farmers. The study proposes an integrated framework connecting IoT-based data collection, predictive analytics, AI-driven decision support, precision agricultural interventions, and sustainability outcomes. The study concludes that AI-enabled sustainable agriculture requires not only technological innovation but also affordable infrastructure, farmer education, interoperable systems, responsible data governance, and policies supporting inclusive technology adoption.
Keywords	Artificial Intelligence, Sustainable Agriculture, Precision Farming, Predictive Analytics, Internet of Things, Smart Agriculture, Agricultural Innovation, Resource Efficiency, Crop Monitoring.
Field	Engineering
Published In	Volume 5, Issue 3, May-June 2023
Published On	2023-05-30

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American Journal of Advanced Multidisciplinary Research and Innovation

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Artificial Intelligence in Sustainable Agriculture: Integrating Precision Farming, Predictive Analytics and IoT

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