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Provided by SIEMENS
SIWA Blockage Predictor identifies abnormal behaviour in a wastewater network and supports automated monitoring and reporting of normal behaviour.
Artificial Intelligence analyses level data collected within manholes on combined or separated systems and in Combined Sewer Overflows (CSO) and warns of anomalies that suggest a blockage or infiltration. With up to two weeks warning companies are given time to optimise their field operations and decision making to prevent spills that should not happen under normal operation. Avoiding these most damaging of spills helps improve the quality of the receiving waters or the built environment.
The AI requires local rainfall data and a level measurement from the monitored asset. Historic level, hydraulic model or network schema are not required.
Monitoring and reporting of normal sewer network behaviour is also easier. SIWA Blockage Predictor provides features to report on asset spillages and sensor health issues.
With SIWA Blockage Predictor customer can:
Offering Overview
Product Name | Base Package | 5 Assets | 25 Assets | 100 Assets |
---|---|---|---|---|
SIWA Blockage Predictor application | ✔ | |||
Base Environment | ✔ | |||
Monitored Sites | 1 | 5 | 25 | 100 |
Time Series Data Storage1 | 1 Year | 1 Year | 1 Year | 1 Year |
Events | 1000 | 1000 | 6000 | 24000 |
1) Time Series Data Storage capacity displayed above will suffice for data collected in the 1st year assuming data is provided at 15 min sampling. Accumulating data beyond 1 year will require purchasing of additional resources.
Siemens AG
RC-GB DI PA LTS
United Kingdom
RC-GB Lighthouse Support
Visit www.siemens.com/water for more information about Siemens' activities in digitalization of the water and waste water industry.