Oral Presentation IPWEA International Asset Management Congress 2024

Innovative Asset Management - How AI is Changing the Game for City of Campbelltown’s Pipe Networks (108355)

Mark Lee 1 , Rhys McQueen 2
  1. VAPAR, Sydney, NSW, Australia
  2. City of Gold Coast , Gold Coast , Queensland, Australia

The City of Campbelltown has a population of 185,000 and manages a wide range of assets to deliver services to the community. This includes a stormwater network valued at $480 million with over 700km of pipes. Effective management of the asset lifecycle of this network requires a combination of engineering prioritisation, cross-team collaboration, and field-based civil works. This presentation case study explores the approach and workflow changes that were implemented to improve efficiency and asset management decision-making resulting from data collected during pipe inspections.

For councils and utilities that run an annual proactive condition assessment program of 20,000m per year, this can produce raw data in the region of:

  • 1,000 video files
    • Hundreds of GB of data

The amount of engineering hours required just to locate and watch this amount of video is significant. In 2021, the Asset Planning team began investigating potential AI solutions to alleviate a selection of monotonous and onerous tasks required using traditional review methods. The goal was to improve data access, reduce review time, and enable engineers to focus on the most critical pipes needing maintenance/rehabilitation.

A key objective of the program was to increase the percentage of pipes inspected annually, with a target to double the inspection rate, ultimately reaching 2% of the stormwater network annually. The 2023-2033 Asset Management Plan set out a Stormwater and Drainage Asset Improvement Plan that would increase the amount of proactive CCTV inspections completed each year.

VAPAR.Solutions has been used by the Campbelltown team to reduce human workload at the beginning of this asset management workflow and present the results in a form that could be easily reviewed by engineers. This case study details how AI and automation can complete these processes and describes the organizational changes at an individual role and task level to achieve improved efficiency and results for both proactive condition assessment and the new pipe asset adoption process.

The user interface includes repair suggestions and the capability to record decisions on next steps directly against each asset, including:
• No action
• Maintenance
• Trenchless rehabilitation
• Dig up repairs


Workflow improvements and streamlined process can now be used to prioritize maintenance activities and prepare capital works programs that align with annual budgets and community service levels.