Accurately and timely detect abnormal events based on the signals from fiber optic vibration sensors installed on the pipeline, improving pipeline management to ensure security and reliability while reducing losses.

Powered by AI technology, build algorithm models based on historical detection data, pipeline attribute data and historical monitoring data, to detect interior corrosion, spot seriously corroded segments, enable cost-effective detection scheduling, ensure safe operation of subsea pipelines, and avoid losses caused by pipeline leakage.

Leverage mathematical tools to explore the correlation between the price and influencing factors based on historical data, so as to discover the price change patterns and forecast the prices in future market rapidly and accurately.

Powered by high-dimensional ML and data mining technologies, build fault warning and diagnosis models and health monitoring models based on various generator indicators, to analyze influencing factors and provide an informed basis for directed inspection and maintenance, maintenance scheduling and cost-effective operation.