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Sewer network management is crucial for urban infrastructure, especially in regions with complex systems. This article presents a case study on the application of AI models to predict levels at a wastewater pumping station. Using real-time sensor data and historical events, an AI model has been developed that improves the accuracy and efficiency of predictions. The goal is to generate an AI model that can predict levels at the water pumping station up to 6 hours in advance, enabling preventive measures. The study demonstrates the potential for generalizing the model to other points in the network, thus improving overall control and management.

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Application of AI Models for Predicting Level in Sewerage Networks: A Case Study of a Wastewater Pumping Station

  • 会议论文

  • 发表日期：

    2026年

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  • Míriam Timiraos,
  • Jesús F. Águila,
  • Óscar Brandón-Basdediós,
  • Andrea Camila Forero,
  • Óscar Fontenla-Romero,
  • José Luis Calvo-Rolle

摘要

Sewer network management is crucial for urban infrastructure, especially in regions with complex systems. This article presents a case study on the application of AI models to predict levels at a wastewater pumping station. Using real-time sensor data and historical events, an AI model has been developed that improves the accuracy and efficiency of predictions. The goal is to generate an AI model that can predict levels at the water pumping station up to 6 hours in advance, enabling preventive measures. The study demonstrates the potential for generalizing the model to other points in the network, thus improving overall control and management.