AI in Vertical Farming: Light and Nutrient Optimization

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ID: 312427
2025
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Abstract
Vertical farming is also quite problematic in regards to energy intensity and accurate nutrient control, which makes it less scalable and sustainable. This paper describes an AI-based optimization system that changes light soils (PAR, far-red, USA) and hydroponic nutrient dosing per-plant needs as they change in real-time. Our network showed a 22 percent reduction in energy consumption and an 18 percent growth in crop yield over that of the static protocols based on a 3-month experiment of lettuce growing. The most significant innovations involve a cheap sensor platform to phenotype plants and a digitally simulated environment to train safe policies. The flexibility of the system to a variety of crops and the possibility of expanding it to large-scale crop production make it a revolutionary instrument of sustainable urban agriculture.
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Authors Imran khurshid, Abdul Majid Soomro, Naeem Aslam, Muhammad Akhtar
Journal Southern Journal of Computer Science
Year 2025
DOI
DOI not found
URL
https://sjcs.isp.edu.pk/index.php/SJCS/article/view/7
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