AI-driven Technology within PermaNET Significantly Reduces False Positives by Accurately Identifying Electrical Noise

Powered by cutting-edge AI technology and intricate algorithms, PermaNET Web has achieved a groundbreaking milestone: automatic identification and categorization of electrical noise within leak audio recordings. This capability enables PermaNET Web to precisely quantify electrical noise within leak audio recordings, presenting it as a percentage, thereby pinpointing the extent to which electrical noise contributes to the overall noise.

PermaNET Web promptly flags the electrical noise calculation alongside the corresponding PermaNET device when the predefined threshold is exceeded. Users can then either confirm or prove false the label and make necessary adjustments to the logger settings. This innovative feature has been designed to aid utilities in swiftly discerning false positives and facilitating the optimization of field resources and network performance through data-driven decision-making.

The implementation of algorithms for identifying and mitigating false positives significantly alleviates the time and costs associated with on-site investigations prompted by leakage alarms. Consequently, resources can be effectively reallocated to address leaks in other critical areas.

Furthermore, integrating the Electrical Noise identification tool with the ‘new leaks’ priority report, which identifies loggers prone to false alarms, further accelerates the process from alarm to pinpointing. This streamlined approach minimizes unnecessary analyst time, resulting in substantial cost savings and conservation of water resources.

Learn more about our PermaNET SU, our acoustic water leak detection logger

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