Reduce Indoor Farming Energy Use with AI Technology
Integrating artificial intelligence into indoor agriculture systems can reduce energy consumption by 25%, helping to feed a growing population. A study by Cornell University engineers published in Nature Food found that AI can optimize lighting and climate control in indoor farms, making them more sustainable. By using AI techniques like deep reinforcement learning, energy use dropped significantly, making food production more efficient and environmentally friendly. The research was supported by various organizations including the U.S. Department of Agriculture and the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship at Cornell.
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Michael Thompson earned his degree in Agricultural Engineering from Purdue University in the USA, specializing in precision agriculture and smart farming technologies. His work revolves around the development of automated systems that increase farm efficiency and reduce environmental impact. Michael is now a senior engineer at a leading agri-tech company, where he designs innovative solutions for modern agriculture.