Automatic metering data analysis: Techniques in loss reduction and control


Conference: Metering, Billing, CRM/CIS Latin America 2005.
Location: Sao Paulo
Presenter: Welson Jacometti and Juliana Rios

After implementing a number of AMR solutions in different utilities, we have learned that the new, larger volume, data flow that AMR contributes to, demands for new ways of not only receiving and forwarding data to proper departments (i.e., engineering, billing, etc.), but also new ways of automatically analyzing it.
In fact, once 100% AMR deployments are still not a reality in many utilities, successful steps towards its gradual implementation requires that automatic metering data analysis systems are in place before AMR itself, and capable of dealing with data that will feed it from manual readings, passing through mobile data acquisition devices, up to remote/on-line data acquisition devices.

Once in place, Metering Data Analysis (or MDA) systems will help to determinate where AMR efforts should be a priority, thus contributing to AMR project success.

The key point is to find out, from metering data acquired by any conventional or automated media, which consumers or meters needs special attention out of thousands or millions of minutes-based candidates.

We would like to present a solution we have developed and organized into a workflow environment, as a complete data analysis system that can be tailored to different measuring systems and, through a number of exception-based inference rules, find out which situations do require human intervention and those that are regular and deserves no further actions. This solution is a step before an artificial intelligence solution that can be trained during operation, and which we are pursuing during the next years.

Along with the technology, we would like as well to discuss the operation methodology that, in this case, represents a paradigm shift in how to manage large consumer databases, loss prediction and prevention, control and – as it succeeds, how it in turn contribute to better quality of services.