American Journal of Advanced Multidisciplinary Research and Innovation

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Volume 8 Issue 5
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Smart Agriculture and Precision Farming: Integrating Artificial Intelligence, IoT and Data Analytics for Sustainable Food Production

Author(s) Charles Chuck Eesley
Country United States
Abstract The rapid growth of the global population, climate variability, declining natural resources, and increasing pressure on agricultural systems have created an urgent need for more efficient and sustainable food-production methods. Smart agriculture and precision farming have emerged as important technological approaches for addressing these challenges. The integration of Artificial Intelligence (AI), the Internet of Things (IoT), remote sensing, cloud computing, and data analytics enables farmers to monitor agricultural conditions, optimise resource utilisation, predict crop performance, detect diseases, and make timely management decisions. This study examines the role of integrated digital technologies in transforming conventional agriculture into a data-driven and sustainable production system. A qualitative and conceptual research methodology based on secondary literature is adopted to examine applications of AI, IoT, and data analytics across crop monitoring, irrigation management, fertiliser optimisation, pest and disease detection, yield prediction, and agricultural supply chains. The study proposes an integrated smart-agriculture framework in which IoT devices generate real-time field data, data-analytics platforms transform raw information into actionable insights, and AI models support predictive and prescriptive agricultural decisions. The analysis indicates that technology-enabled precision farming can potentially improve productivity while reducing water, fertiliser, pesticide, energy, and labour requirements. However, adoption is constrained by high initial investment, inadequate rural connectivity, limited digital literacy, fragmented agricultural data, cybersecurity concerns, and unequal access to advanced technologies. The study concludes that sustainable smart agriculture requires not only technological innovation but also farmer training, affordable infrastructure, interoperable data systems, supportive policies, and human-centred implementation.
Keywords Smart Agriculture, Precision Farming, Artificial Intelligence, Internet of Things, Data Analytics, Sustainable Agriculture, Digital Agriculture, Crop Monitoring, Agricultural Innovation, Food Security.
Field Engineering
Published In Volume 5, Issue 2, March-April 2023
Published On 2023-03-02
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