TL;DR:
- Melbourne Water employs IoT sensors, a unified data platform, machine learning, and a digital twin to predict recycled water quality two days in advance with 75% accuracy.
- The initiative aims to provide early warnings for users of Class A recycled water and mitigate the impact of water clarity issues.
- IoT technology and a virtual model were used for real-time insights before predictive analytics.
- The unified data platform combines Snowflake and AWS services for comprehensive data management.
- A digital twin, utilizing AWS IoT SiteWise and Amazon SageMaker, predicts the impact of various factors on water quality.
- Melbourne Water is proactively addressing water quality issues and ensuring seamless production resumption.
- The project aligns with Melbourne Water’s broader vision of expanding its IT, OT, and IoT capabilities.
- It reflects a market trend towards data-driven solutions for water resource management.
Main AI News:
In an era where data reigns supreme, Melbourne Water is leading the charge with cutting-edge technology and innovative strategies to ensure the quality of its recycled water never falters. With the help of IoT sensors, a unified data platform, machine learning, and a sophisticated digital twin of its treatment plants, Melbourne Water has embarked on a journey to predict recycled water quality with impressive precision, providing valuable insights two days in advance, and achieving a remarkable 75 percent accuracy rate.
A Vital Resource for Various Sectors
Melbourne Water recognizes the vital role its Class A recycled water plays in supporting farmers, companies, and households for non-drinking purposes. Ensuring the consistent quality of this water is paramount to its users’ operations. Blair Smith, the Innovation Lead at Melbourne Water, underscores the significance of this endeavor, particularly in predicting turbidity, a crucial measure of water clarity. If water clarity falls below acceptable standards, production may be impacted, necessitating alternative water sources.
The IoT Revolution
Before delving into predictive analytics, Melbourne Water had already invested in IoT technology and developed an in-house virtual model to gain real-time insights into treatment plant discharges. The organization’s commitment to innovation is evident in its deployment of advanced technology, such as an automatic identification system (AIS) and GPS monitoring devices on a buoy at Boags Rocks. This buoy captures live data regarding water quality at this critical discharge point, facilitating the calibration of a sophisticated 3D hydrodynamic model.
A Unified Data Platform
The journey toward predicting water quality is anchored in Melbourne Water’s ‘Intelligent Network Enablement’ program. Partnering with AWS specialist Arq Group, Melbourne Water sought to create a unified data platform that would provide a comprehensive view of all data sources from a single vantage point. Utilizing a combination of Snowflake and AWS services, including a data lake and analytics platform called the unified data store, Melbourne Water now enjoys enhanced capabilities for data ingestion, transformation, and reporting.
Harnessing the Power of Digital Twin and Machine Learning
The unified data platform paved the way for Arq to construct a digital twin of Melbourne Water’s recycled water production processes. This virtual model leverages AWS IoT SiteWise to collect and analyze real-time IoT sensor data, laboratory data, and crucial weather data. Armed with this wealth of information, Amazon SageMaker comes into play, providing machine learning models capable of predicting the impact of various factors on water quality.
A Brighter Future for Water Quality
Thanks to these groundbreaking innovations, Melbourne Water has transitioned from merely having real-time data to predicting water quality two days in advance, boasting an impressive 75 percent accuracy rate. Blair Smith sums up the transformation succinctly, stating, “We have an accurate three-day outlook on turbidity and other conditions that impact our recycled water production.” This newfound capability allows Melbourne Water to address water quality issues proactively, ensuring a seamless resumption of production when conditions permit.
A Visionary Roadmap
This remarkable project aligns seamlessly with Melbourne Water’s broader vision of expanding its IT, OT, and IoT capabilities. Arq Group is set to embark on another digital twin project, this time incorporating real-time video analytics for drones. This initiative is part of Melbourne Water’s ongoing commitment to its ‘Intelligent Network Enablement’ program, which builds on the foundations of a prior digital transformation strategy initiated in 2017. In this earlier endeavor, historical data was harnessed to optimize water pumping routes, while IBM’s cloud platform for computer vision was employed to detect blocked grates.
Conclusion:
Melbourne Water’s advanced technology-driven approach to predicting water quality sets a precedent in the market. It demonstrates the potential for IoT, data analytics, and digital twins to enhance resource management, reduce operational disruptions, and ensure sustainability in essential sectors reliant on water resources. This innovation highlights the growing importance of data-driven decision-making for organizations across various industries seeking to optimize their operations and achieve environmental goals.
