CCWI2017: F94 'Valve Status Verification and Sensor Error Detection via Causal Inference from Sensor Data'
journal contributionposted on 01.09.2017 by Dirk Vries, Joost van Summeren
Any type of content formally published in an academic journal, usually following a peer-review process.
Recent developments in (near) real-time sensor applications have the potential to provide operators and managers with useful information on drinking water distribution supply and need of its maintenance. A systematic methodology based on causal inference from observational data is proposed to increase knowledge of water supply distribution systems equipped with sensor networks. This methodology can be used to help identify deviations from expected operation of water supply and sensor infrastructure, using only observational data. We outline the first steps of two distinct procedures that use data from a sensor network, to infer a map of a causal dependence structure. These procedures are applied to scenario studies where an unexpected change in operation occurs, i.e. a valve status is different and a sensor bias is introduced. A draft outline of future steps is given that could improve and validate the methodology.