Mott MacDonald is a global engineering, management, and development consultancy that plans, designs, builds, and maintains infrastructure. It has a focus on digital solutions, including, AI, machine learning and data services. In New Zealand it is assisting Auckland Council in gaining the most from its assets, leveraging data-driven insights to inform decision-making.

Challenge/Situational Overview

Industry Context Following the amalgamation of eight councils into the ‘super city’ 14 years ago, Auckland Council’s Healthy Waters team focused on improving the collection, standardisation and management of their data sets. One of the key challenges with this approach was not just deploying new technologies, but identifying, validating, organising and assessing the quality of the data spread across siloed systems. As data surfaced, quality issues emerged, requiring iterative improvements to ensure it was AI ready. To better serve its citizens, the Council needed a more efficient way to integrate important datasets.

Technical Problem

Identifying, validating, organising and assessing the quality of the data from many siloed data sets.
Surfacing the data exposed quality issues which required iterative improvements to make it technology ready.
The Council needed a better way to bring important datasets together to better serve the citizens of Auckland.

Solutions Approach

Fast forward to 2025 and the strong data management discipline that Council has developed is proving valuable in the age of AI. Today, the team has implemented several AI and machine learning (ML) applications that are enhancing service delivery and greater value to Aucklanders. This case study examines multiple interrelated solutions, including identifying pipe blockages, and predicting pipe conditions.

Implementation

• Image processing for pipe blockages:  Auckland Council in collaboration with Mott MacDonald and Lynker Analytics has developed an innovative AI-powered system to enhance stormwater management. The solution combines simple wildlife outdoor cameras with AI to monitor, analyse and consolidate data on pipe blockages and flooding at the city’s most critical stormwater structures.

 

• Pipe condition prediction: Using the existing dataset of stormwater pipe inspections, the team have also developed a machine learning model to assess the condition grade of pipes over their lifespan. This hybrid machine learning model predicts the age at which a pipe will deteriorate, aiding Council to better plan their asset renewals and target this spending more effectively.

 

Innovation Factor

By detecting blockages, the system helps create a more sustainable and resilient stormwater network, while improving maintenance team productivity, reducing costs and minimising disruptions to the public. Previously, these discharge sites had to be manually inspected on rotation especially before major rainfall events. The new AI-driven approach streamlines monitoring, enhances efficiency and ensures faster response times.
Predicting pipe lifespan and condition grades enables proactive renewal planning, optimising investment and reducing costly reactive maintenance.

Outcomes & Impact

Broader benefits:

These initiatives provide valuable insights for Auckland stormwater management and benefits for the wider community, additionally these insights act as building blocks for further innovation and improvement of stormwater management and network operations.

Scalability:

The advances that Auckland is now realising through AI technologies have been made possible through the hard work put in over the past decade to organise and enhance their data and build an ecosystem of aligned service providers.
This approach has driven effective collaboration across the supply chain ecosystem using digital mediums to develop and deploy these new services leveraging an organised and well-managed data system.

Key Learnings & Future Applications

Technical insights:

AI and data integration unlock opportunities to improve public services and maximise the value of existing infrastructure.

Industry implications:

Success depends on strong data and information management foundations, this is where the greatest effort and investment are required.

Mott MacDonald | mottmac.com