AI Predictive Assessment & Sewer Index for Sewer Networks (AIX)

Project aim and objectives

The aim of the project is to develop a data-driven AI model and a standardized Sewer Index for status assessment and predictive maintenance of sewer networks.  This will enable water and wastewater organizations to identify high-risk pipelines, optimize maintenance and reinvestment planning, and improve the long-term resilience of the infrastructure through standardized, cost-effective, and proactive management. 

The project aims to: Identify and classify necessary data: Determine which data is required and which additional data is valuable for AI-based status assessment of the pipeline network. 

• Develop a predictive AI model: Train and validate an AI model, to predict the probability of specific pipeline damage on uninspected pipelines, followed by evaluation and improvement. 
•  Establish a Standardized Sewer Index (AIX): Discuss, propose, and define a quantifiable index that complements subjective assessments. 
• Generate an AI model for Sewer Index: Develop and validate an AI-based model to calculate the sewer index for uninspected pipes and adjust it based on analyses and evaluations.

Expected Benefits

• Proactive identification of high-risk pipes, even in sections lacking prior inspections.
• Optimized maintenance planning and resource allocation based on probability-driven risk assessments.
• Adoption of a uniform Sewer Health Index that offers a clear overview of network status and supports long-term budgeting.
• Significant cost savings in condition assessment, while extending sewer network lifespan and operational reliability.