The AI portal serves as a comprehensive platform for water leak management, leveraging sophisticated regression and classification models to detect and analyze leaks with unprecedented accuracy. By processing data collected from various sensors, the portal identifies leak locations and sizes, enabling users to visualize and prioritize repair tasks effectively. The dashboard interface provides a clear overview of leak statuses, historical data, and predictive insights, facilitating swift decision-making and resource allocation for field engineer dispatch.

Tasks for Achieving This

1. Data Integration: Ensure seamless integration of sensor data into the portal, supporting real-time analysis and detection capabilities.

2. AI Model Implementation: Develop and integrate AI models for regression (to estimate leak sizes) and classification (to identify leak occurrences), utilizing a robust dataset for training and validation.

3. Dashboard Development: Design an intuitive and informative dashboard that displays leaks in a user-friendly format, including severity, location, and actionable insights.

4. Engineer Dispatch System: Create a system within the portal for users to assign and dispatch field engineers to leak sites, including scheduling and task management features.

5. Performance Monitoring and Feedback: Implement tools for monitoring repair effectiveness and collecting feedback, using this data to refine AI models and improve portal functionality.

Expected Result

The deployment of the AI portal is anticipated to:

• Dramatically enhance the efficiency and accuracy of leak detection and management processes, reducing water loss and associated costs.

• Enable users to make informed decisions quickly, prioritizing repair actions based on the severity and location of leaks as identified by AI analysis.

• Streamline the dispatch of field engineers, optimizing repair times and resource use through a centralized management system.

• Foster continuous improvement in leak detection and repair strategies through data-driven insights and machine learning adaptations.