AI Revolutionizes Energy Efficiency in Indoor Farming for a Sustainable Future

Artificial intelligence (AI) is playing an increasingly important role in improving the sustainability and efficiency of indoor agriculture, offering the potential to reduce energy consumption significantly. According to recent research conducted by engineers at Cornell University, integrating AI into today's environmental control systems could reduce energy consumption for indoor farming by as much as 25%. This advancement is crucial as the world's population is expected to reach 9.7 billion by 2050, demanding new solutions to address food production challenges.

Indoor agriculture, mainly plant factories with artificial lighting and climate control, provides a promising alternative to traditional farming, especially in the face of climate change. However, these systems are notoriously energy-intensive, making it vital to find ways to optimize their efficiency. According to Benjamin Decardi-Nelson, a postdoctoral fellow in the laboratory of Fengqi You, the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering at Cornell, the incorporation of AI into large-scale indoor farms could enhance crop photosynthesis, transpiration, and respiration, ultimately leading to substantial reductions in energy use while boosting efficiency and conserving valuable resources.

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The study "Artificial Intelligence Can Regulate Light and Climate Systems to Reduce Energy Use in Plant Factories and Support Sustainable Food Production" was published in Nature Food. It demonstrated that AI could play a critical role in helping indoor farms manage key factors like lighting, ventilation, and temperature control to create optimal crop growth conditions. AI tools like deep reinforcement learning and computational optimization were used to analyze lettuce cultivation in indoor agricultural facilities across a variety of locations, including Los Angeles, Chicago, Miami, Seattle, Milwaukee, Phoenix, Fargo (North Dakota), Ithaca (New York), Reykjavík (Iceland), and Dubai (United Arab Emirates).

Using AI to optimize environmental control systems, the energy required to produce one kilogram of indoor-grown lettuce dropped from 9.5-kilowatt hours to 6.42-kilowatt hours in regions using AI-powered systems. For warmer climates, such as Dubai and certain southern U.S. regions, energy consumption was reduced from 10.5 kilowatt hours per kilogram to 7.26 kilowatt hours per kilogram. The study highlighted the importance of regulating ventilation and lighting to maintain ideal conditions for photosynthesis, oxygen for respiration, and overall plant growth. Low ventilation during simulated daylight hours (16 hours of light) and high ventilation during the simulated night (eight hours of darkness) proved an effective energy-saving strategy.

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Ventilation, while crucial for reducing energy use, also complicates plant growth by affecting carbon dioxide levels and moisture balance. AI tools can efficiently manage these complexities, offering a promising solution for balancing energy consumption with the demands of indoor farming. Existing environmental control systems in plant factories lack the sophistication needed to address these challenges, making AI an essential innovation for the future of sustainable indoor agriculture.

As the research shows, AI can make indoor farming viable even in regions with limited energy-saving opportunities. The technology streamlines operations, reduces energy consumption, and offers scalable solutions for feeding a growing global population. Forward-thinking AI applications in agriculture may help mitigate the impact of climate change while addressing global food security challenges.

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The U.S. Department of Agriculture's National Institute of Food and Agriculture, the Natural Sciences and Engineering Research Council of Canada, and the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship at Cornell funded the research.