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Artificial intelligence for optimizing and automating power plants

Artificial intelligence for optimizing and automating power plants

Power plants run at 33% efficiency, factories don't fare much better. By measuring all the conditions that impact combustion levels in real time we can make the adjustments necessary to get the maximum amount of energy out of fuel. How it works is we take all the existing sensor data, add our own proprietary IIoT sensors and then recreate the plant or factory as a digital twin to run a recurrent neural net to establish the optimal settings. Then the system uses this data in real time with the incoming sensor data to optimize production. Our early test shows a saving of 3-5% in efficiency. Saving fuel, saving money, and reducing emissions.
Game Theory blog contributor for the Economist, developed machine learning algorithms at QM University in London. Oxford for Social Science of the Internet.
Founder Thermo.Ai • Author of Secrets of Advertising to Gen Y Consumers (2010) Contributor to VentureBeat's AI section, author of The AI Entrepreneur.

Carolina Chaves

Avatar for Carolina Chaves
COO at ThermoAI, Chemical Engineer of Colombian Nacional University, researcher at TAYEA (Termodinámica Aplicada y Energías Alternativas)

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