Effects of Deep Predictor Implementation: Energy Cost Optimization
By optimizing energy costs, energy consumption is reduced. This leads to improved profitability with cost savings amounting to several tens of millions of yen annually.
One of the challenges that our no-code AI predictive analytics service "Deep Predictor" addresses is "energy cost optimization." AI learns the patterns of energy consumption from past operational data. It identifies the conditions for equipment settings to minimize energy consumption. Additionally, by analyzing complex patterns and codifying knowledge, it helps in the accumulation and inheritance of veteran know-how. 【Required Data】 ■ Weather Data: Temperature, humidity, wind speed, etc. ■ Equipment Data: Operating status and historical settings of devices and systems ■ Economic Indicator Data: Analyze economic indicators and market trend data as needed, considering them as factors of variation. *For more details, please download the PDF or feel free to contact us.
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