O USO DA INTELIGÊNCIA ARTIFICIAL NA DETECÇÃO DE FRAUDES EM ALIMENTOS: UMA REVISÃO DE LITERATURA

Abstract

This literature review focuses on the application of Artificial Intelligence (AI) in food fraud detection. AI uses advanced machine learning algorithms to analyze large volumes of data in real time, identifying suspicious patterns that may indicate food adulteration, labeling fraud, or other fraudulent practices. This technology not only strengthens supply chain surveillance protocols but also acts as a barrier to protect public health and preserve market integrity. In addition to detecting irregularities, AI employs predictive analytics to anticipate potential fraud, allowing for the implementation of proactive preventive measures. However, challenges such as data quality and the need for appropriate regulations are critical considerations that need to be addressed to maximize the benefits of AI in the food industry. As technology advances, new innovations in AI are expected to expand its capabilities in food safety, ushering in an era of transparency and safety in food production and distribution globally.