American Journal of Advanced Multidisciplinary Research and Innovation

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Digital Technologies for Sustainable Agricultural Productivity

Author(s) Leslie Pack Kaelbling
Country United States
Abstract Digital technologies are transforming modern agriculture by enabling data-driven, resource-efficient, and climate-resilient farming systems that improve productivity while supporting environmental sustainability. The integration of Artificial Intelligence (AI), Internet of Things (IoT), Precision Agriculture, Machine Learning (ML), Geographic Information Systems (GIS), Global Positioning System (GPS), Remote Sensing, Drones (UAVs), Cloud Computing, Big Data Analytics, Blockchain, Edge Computing, and Digital Twins has significantly enhanced agricultural decision-making, crop monitoring, irrigation management, pest and disease detection, soil health assessment, livestock management, and supply chain transparency. These technologies facilitate precision farming, reduce resource wastage, optimize fertilizer and pesticide application, conserve water, improve crop yields, and strengthen food security under changing climatic conditions.
This study investigates digital technologies for sustainable agricultural productivity using a multidisciplinary perspective. A qualitative and analytical research methodology based on secondary data from agricultural science, environmental science, information technology, engineering, economics, and rural development literature is employed to examine digital agriculture frameworks, implementation strategies, technological innovations, governance mechanisms, challenges, and future research opportunities. Particular emphasis is placed on smart farming, climate-smart agriculture, AI-powered decision support systems, precision agriculture, blockchain-enabled traceability, digital advisory services, and sustainable resource management.
The findings indicate that digital technologies significantly improve agricultural productivity, resource-use efficiency, climate resilience, food quality, farm profitability, and environmental sustainability. Intelligent farming systems enable real-time monitoring, predictive analytics, automated irrigation, yield forecasting, disease detection, and transparent agricultural supply chains while supporting the achievement of the United Nations Sustainable Development Goals (SDGs). However, challenges including digital infrastructure limitations, high implementation costs, data privacy concerns, cybersecurity risks, digital literacy gaps, interoperability issues, and policy constraints remain significant barriers to widespread adoption. The study concludes that integrating Artificial Intelligence, precision agriculture, IoT, remote sensing, cloud computing, and interdisciplinary collaboration provides a comprehensive pathway toward resilient, productive, and sustainable agricultural systems.
Keywords Digital Agriculture, Precision Agriculture, Artificial Intelligence, Internet of Things, Sustainable Agriculture, Smart Farming, Remote Sensing, Climate-Smart Agriculture.
Field Engineering
Published In Volume 3, Issue 6, November-December 2021
Published On 2021-12-31
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