Revolutionizing crop production: AI-driven precision agriculture, vertical farming, and sustainable resource optimization

Sustainable agricultural practices are becoming increasingly vital as the global population keeps rising at an unprecedented rate. In light of the ongoing climate crisis, the frequency of extreme weather events has intensified, posing significant threats to farmers and their livelihoods across the globe. As these challenges multiply, many traditional agricultural methods struggle to keep pace, highlighting the necessity for innovative solutions. These new sustainable practices can be quite complex and often present challenges for farmers to implement effectively. This may be attributed to various factors, including a lack of willingness to change established methods, accessibility issues regarding new technologies, or even a deficit in knowledge about how to adopt these practices successfully. In this context, the potential for using cutting-edge technologies in agriculture becomes increasingly relevant. These technologies offer promising alternatives that can simplify various processes, such as planning and modelling agricultural practices, thereby making it easier for farmers to adapt. For instance, a mixed reality headset could serve as an invaluable tool by providing users with detailed information about optimal planting spacing between seeds. This type of immersive technology can enhance understanding and application in the field. On a different note, unmanned aerial systems, commonly known as drones, could be employed to gather NDVI (Normalized Difference Vegetation Index) data. This data is crucial, as it enables a more in-depth analysis of crop production, giving farmers actionable insights into their agricultural practices. It is important to consider three hypothetical factors that may hinder the adoption of these technologies: price, motivation, and knowledge. To evaluate the impact of price alongside other technological factors, a systematic approach might include a second round of analysis focused specifically on motivation. Meanwhile, the final round of analysis could completely omit all prior explanations to gauge raw responses effectively. In terms of practical applications, these technologies could play a significant role at three different stages of system development. First, they can assist users in comprehending the technology, facilitating proper training to maximize their efficacy. Second, these systems can help assess whether additional factors or technologies are necessary for achieving similar results in agricultural productivity. Finally, such technologies could serve as a form of external analysis, evaluating the potential future applications of the agricultural system. Altogether, the implementation of these advanced methods provides a rigorous assessment and serves as compelling proof of the significance, feasibility, and innovative nature of this ongoing study in sustainable agriculture. (Chowdhury et al., 2023) [4].