As part of an ongoing process to improve stormwater asset maintenance across the city, Auckland Council initiated the installation of a camera network across more than 50 stormwater assets.

The goal of this network is to produce monitoring data that is then used to train Artificial Intelligence (AI) software to recognise different categories of blockages and alert maintenance contractors to the asset issues, allowing swifter reaction times to emerging issues.

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Morphum was brought in to support this project’s implementation. Our team were able to assess and prioritise the asset selection that would be monitored to provide the deep learning AI the data it requires, before beginning the installation process.

Coordinating with Healthy Waters (Auckland Council), Glasgow’s Contractors, Basins Environmental, Mott MacDonald and Lynker Analytics all together, we were able to ensure all contractors and data recipients were provided the information required to implement the network across the city and we supported the consenting process throughout the project.

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To ensure the most positive results, the operations team conducted construction audits and continue to provide ongoing engineering support with the camera network.

With this on-site ability to collect data and monitor priority stormwater assets for maintenance, the risk and frequency of flooding has been reduced.

The deep learning AI has the potential in future to incorporate more sites into the monitoring framework, not just in Auckland, but can be used as a case study to implement systems around NZ & Australia using similar data collection networks. There are also an additional 200 sites that have been flagged as potential areas for AI monitoring implementation that are currently being scoped into a future Healthy Waters project.

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