The objective of the study is to prevent the sterilization of soils intended for harvesting. This objective will be realized through the implementation of Artificial Intelligence (AI) to regulate and oversee biotic and abiotic elements, optimize the utilization of natural resources, and mitigate the adverse environmental impact. The implementation of Precision Agriculture (PA) constitutes an innovative practice, integrating advanced technologies with the objective of optimizing agricultural resources and minimizing environmental impact. This innovative agricultural management system empowers producers to make informed and specific decisions for each section of their fields. Furthermore, the combined implementation of vertical farming represents a viable approach within the context of sustainable agriculture. This approach solves problems of land scarcity, environmental consequences and food security. The agent-based model employs bibliometric indicators as research agents in sustainable agriculture, thereby assisting decision-makers in formulating public policies that support sustainable agricultural practices. The model employs various scenario simulations to achieve this.

The use of AI and machine learning is a process that involves the analysis of large volumes of data to generate predictive models, recommendations and automated processes. This is achieved using the Internet of Things (IoT) and cloud computing, as well as the integration of devices, sensors and systems for remote monitoring and control. Examples of the use of technological systems include field sensors and wireless sensor networks. These systems measure variables such as soil moisture, temperature and nutrients. They then adjust input according to the real needs of the crops.