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Smart Agriculture Technologies for Sustainable Food Production

Author(s) Juan Jesús Medrano
Country Spain
Abstract Smart agriculture technologies are transforming contemporary food production by integrating digital technologies, intelligent decision-making systems, precision farming, connected sensors, remote sensing, automation, artificial intelligence, and data analytics into agricultural practices. Increasing pressure on land, water, energy, and agricultural resources has created a need for production systems that improve productivity while reducing environmental impacts. This study examines smart agriculture technologies for sustainable food production, focusing on precision agriculture, Internet of Things applications, artificial intelligence, machine learning, remote sensing, agricultural robotics, smart irrigation, predictive analytics, and digital farm management. A qualitative descriptive and conceptual research design was adopted using secondary academic literature. The analysis considers how technology-enabled agricultural systems can support crop monitoring, soil assessment, irrigation optimization, pest and disease detection, yield prediction, resource management, and agricultural decision-making.
Smart sensors can provide real-time information regarding soil moisture, temperature, nutrients, and crop conditions, while satellite and drone imagery can support large-scale crop monitoring. Artificial intelligence and machine learning can process agricultural datasets to identify patterns and support predictive decision-making. Automated machinery and agricultural robotics can improve operational precision and reduce dependence on repetitive manual activities. However, adoption remains affected by high technology costs, limited digital infrastructure, technical skills, interoperability issues, data-management concerns, and unequal access to advanced agricultural technologies. The study emphasizes integrated smart agriculture frameworks that combine sensing, connectivity, analytics, automation, and sustainable resource management. Such approaches can contribute to efficient use of water, fertilizers, energy, and land while supporting agricultural productivity. Future research should focus on affordable smart technologies, explainable artificial intelligence, autonomous farming systems, climate-resilient agriculture, integrated farm data platforms, and scalable solutions suitable for diverse agricultural environments.
Keywords Smart Agriculture, Sustainable Food Production, Precision Agriculture, Artificial Intelligence, Internet of Things, Agricultural Technology, Machine Learning, Remote Sensing, Smart Irrigation, Sustainable Farming
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-23
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