TRANSFORMANDO A AGRICULTURA: PRINCÍPIOS FUNDAMENTAIS E DESAFIOS DA INTELIGÊNCIA ARTIFICIAL

Abstract

Modern agriculture seeks efficiency and sustainability by driving the integration of intelligent automation and management systems. These systems process data to monitor crops, enabling precise application of inputs at variable rates. This approach, aligned with environmental considerations, aims to increase food production in response to global population growth. The widespread adoption of these intelligent systems is anticipated, promising to be more effective and sustainable than conventional agricultural management methods. This study focuses on establishing the fundamental principles of artificial intelligence (AI) in agriculture, aiming to support the evaluation of applied concepts and pave the way for more specialized analyses of successful AI implementations in this sector. It is an analytical review of the application of artificial intelligence in agricultural production systems, based on a literature review. Data were collected from the Science Direct database, covering articles published between 2019 and 2023 to provide recent information. The inclusion criteria involved articles with descriptors such as "agriculture production systems" and "artificial intelligence." The full adoption of artificial intelligence in agriculture faces fundamental challenges, such as the need for reliable data, farmers' resistance to new technologies, inadequate infrastructure in some agricultural regions, and concerns over data security. Overcoming these challenges is essential to unlocking the full transformative potential of artificial intelligence in agriculture, facilitating more sustainable and efficient production in the face of growing global food demands.