<![CDATA[Agriculture plays a crucial role in fulfilling global food needs and promoting societal well-being. Soybean cultivation, as a strategic food crop, offers essential protein sources for humans and livestock while enhancing soil fertility through nitrogen fixation. However, the increasing global demand for soybeans poses challenges for farmers, particularly in terms of cultivation efficiency. These challenges are further exacerbated by climate change, land use, disease threats, and commodity price fluctuations. The advancement of agricultural technology, such as IoT, remote sensing, artificial intelligence, and predictive modeling, holds significant promise in improving soybean cultivation's efficiency and productivity. Precision agriculture emerges as a pivotal approach to support agricultural efficiency, productivity, and profitability. Expert systems and image processing techniques like artificial neural networks and genetic algorithms play a vital role in implementing precision agriculture. Information technology's use in precision agriculture focuses on data collection, analysis, and application in farming. Despite considerable research proposing technology integration in soybean cultivation, comprehensive studies on its potential integration remain limited. Thus, this international research aims to analyze the prospects of integrating agricultural technology into plant monitoring systems. Its primary goal is to contribute to the development of sustainable and efficient agricultural practices, considering environmental conditions and natural resource potentials. The findings will serve as a strategic foundation for agricultural stakeholders and policymakers to enhance soybean cultivation's sustainability, productivity, and quality, while effectively addressing global food challenges in the future.]]>
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