This study aims to conduct a systematic and comprehensive literature review on the applications of artificial intelligence and machine learning in vertical farming, focusing on technology optimization, economic aspects, and environmental sustainability. The method used is a systematic literature review (SLR) of open-access academic publications from reputable international databases such as Scopus, Web of Science, and Google Scholar, with a publication timeframe spanning the last five years (2018-2023). The review results indicate that the most widely applied soilless cultivation technologies are hydroponics, aeroponics, and aquaponics, with aeroponics demonstrating the highest water use efficiency. The integration of IoT, smart sensors, and AI can increase crop productivity; however, the carbon footprint of these systems is highly dependent on the energy source used. The main barriers to adoption are high initial investment and operational energy costs. This article contributes to updating and expanding the understanding of the applications of artificial intelligence and machine learning in vertical farming, as well as identifying research gaps and proposing directions for technology and policy development oriented towards sustainability and profitability
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