Sewer Diagnosis: AI for Predictive Maintenance Scheduling

In a recent case, a utility struggled with unexpected sewer failures due to insufficient maintenance scheduling. Frequent repairs were costly and disruptive, so the team turned to WaterGuru to help prioritize sections most in need of attention.

WaterGuru analyzed real inspection data, scoring sections based on condition and usage frequency, and predicted the urgency of maintenance needs. For example, sections with lower condition scores and high urgency scores were scheduled for immediate repairs, while others were assigned a less frequent maintenance cycle. This proactive approach helped reduce unexpected failures and maintenance costs significantly.

The dataset includes actual inspection dates, condition scores, and cost estimates, offering a real-world basis for predictive maintenance.