Business Challenge: Power plant systems are one of the most complex and expensive systems, hence they must function efficiently round the clock. Tiny anomalies in the power system at times result in huge loss in terms of infrastructure, time and money..
By performing deep learning based data-driven models over historical data collected from the record of IoT devices of power plants, anomalies can be detected on time hence damage can be reduced.
Based on the results generated using the historical data, an alarm will be triggered to pre-warn the authorities before an anomaly appears in the system.
Anomalies would be detected at early stages resulting in no loss of time, money and efficiency of the power plant. Moreover, maintenance of the plant can be performed timely.
With anomalies being detected on time, the power plant would not suffer the loss of time, efficiency and resources. Plant productivity is creased by 10-15%.