ARTIFICIAL INTELLIGENCE IN AGRICULTURE 4.0: CHALLENGES, POTENTIALS, AND APPLICATIONS IN CROP MONITORING AND MANAGEMENT

Abstract

This article analyzes the main applications, potentialities, and challenges of Artificial Intelligence (AI) in crop monitoring and management within the context of Agriculture 4.0. The study is characterized as a qualitative bibliographic review based on scientific publications and technical materials related to digital agriculture, artificial intelligence, and technologies applied to the agricultural sector. The analysis showed that AI has relevant applications in crop monitoring, identification of pests, diseases and weeds, irrigation management, yield prediction, and decision-making support. These technologies can contribute to more accurate crop monitoring and more rational use of agricultural resources. However, their adoption still faces challenges related to data quality and availability, implementation costs, technological infrastructure, connectivity, and user training. It is concluded that AI has the potential to make agriculture more efficient, precise, and sustainable, provided that it is integrated with technical knowledge and the actual conditions of agricultural production.