Implementing AI-driven predictive maintenance on energy-intensive equipment reduces consumption by 15% through optimized usage patterns and real-time monitoring.
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In this initial stage of energy management, businesses actively monitor their current energy consumption patterns. This involves tracking the amount of electricity or gas used by different departments, machines, and systems within the organization. The goal is to identify areas where energy usage is high or inefficient. Data on energy consumption can be collected from various sources, including utility bills, meter readings, and data from building management systems (BMS). By gathering this information, businesses can gain a clear understanding of their current energy profile. This knowledge will serve as the foundation for making informed decisions about reducing energy costs and implementing more efficient practices in subsequent stages. A thorough analysis of energy consumption helps companies to pinpoint opportunities for improvement.
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