Published: Nov 30, 2023
digital twin - sustainable water
NCS helped Melbourne Water ensure a consistent and low-carbon method of providing quality water supply to the city’s 5 million inhabitants. This engagement employs machine learning and analytics to determine causes to poor quality of water supply and helps predict when supplies must be switched to maintain water quality. NCS enabled this cloud-based solution, using data from more than 700 tags to give up to an 80% prediction accuracy within 72 hours of the potential disruption.
The challenge:
Melbourne Water has responded to the need of more water supply with Class A recycled water. However, when the turbidity of water affects recycled water production, there is a lack of warning to the operation teams and customers.
The solution:
NCS and its partner jointly created a cloud-based digital twin that models the end-to-end process of the recycled water production, aggregating data from across different platforms. This helps predict conditions that may impact the recycled water production, providing greater certainty for recycled water supply and improving customer communication.
Snapshot of capabilities:
- Machine Learning & Predictive Analytics
- Digital Twin
The impact:
The digital twin provides 3-day advanced warning or critical turbidity, providing early warning to operation teams and customers, as well as when recycled water production can resume.