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:

• Store, analyse and compare level data of a fleet of sewage assets
• Detect potential blockages in CSO and Manholes as they are forming
• Reduce the number of false positive alerts they are receiving for sewer blockages
• Manage ticket workflows for developing problems 
• Improve data quality and sensor management
• Monitor and Report on the spill performance of their overflow assets