James Bailey (left) and Dr Ed Keedwell (right) receive the award from Professor Bogumil Ulanicki 

Award for Centre for Water Systems Knowledge Transfer Partnership Associate

The project has used sewer asset data and historical incident data to predict the risk of a blockage on the wastewater network, using data mining techniques. 

The project’s aim is to help DCWW prioritise proactive maintenance of the wastewater network and provide verification of the data mining techniques used on the real-world data of DCWW. At the closing ceremony the presentation and paper, entitled ‘Predictive Risk Modelling of Real-World Wastewater Network Incidents’, were awarded ‘second best student paper’ at the conference by the organising committee. 

Date: 10 September 2015

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