The detector who cried event, or the importance of really advanced flow tracking.

In NRW management, working hard to get predictions right saves time, money and water.

Multiple factors are at play in the effective detection of water distribution network events. The key features that enable a software to pick up true events, but avoid crying wolf too frequently, can be hard to spot at first glance. It all begins by being good at establishing normality, i.e., at knowing what the zone's consumption at the next time step is going to be with a sufficiently narrow dispersion band.

If that band is not narrow enough, it's much harder to tell with an acceptable degree of confidence that this value we are seeing is normal, or not normal (and therefore, potentially indicative of an event). For the event management algorythm, the key decision at that point is to know when not to issue a notification, if it cannot reliably ensure something is escaping normality – just a hunch is not good enough.

Detecting events on wide bands is likely to generate too many false positives. Of course, wide dispersion is often unavoidable on flow predictions, and there is little that can be done – except to avoid generating false notifications that will only drive users' confidence away. It is for this reason that our researchers and datascientists at Baseform work hard to leverage our Big Data trove (over 40 thousand years of real-time flow monitoring experience and over 1 million events detected) as our predictive engines learn daily how to not cry wolf in vain.

In NRW management, working hard to get predictions right saves time, money and water.

Get in touch to find out how your utility can also benefit from Baseform.