An alliance of businesses in the business of water

Smart Water Awards 2018 - Innovation in SMEs Award nominees

May 28, 2018

Sponsored by SA Water

The Innovation in SMEs Award recognises small and medium-sized businesses that have fostered innovation an organisation that has fostered innovation to solve a significant environmental and/or water resource related problem; develop a product, solution or service; undertake research or trial applications; share, communicate and ensure acceptance and take up of new knowledge, technology or research; improve manufacturing or business processes and/or improve sales, promotion and product/service delivery.


Project: Big Data Analytics for Efficient Utilities

Optimatics and the California Water Service Company (Cal Water) collaborated to develop a unique optimal risk-based approach for capital planning and asset management for Cal Water’s Visalia network. The developed approach involved a criticality analysis performed with the Optimatics software – OptiCritical – which simulates the effects of a pipe breakage and subsequent pipe isolation on a water distribution system. A system-wide OptiCritical pipe criticality analysis was run to automatically step through the network model breaking and isolating each pipe in turn and running a hydraulic analysis for each scenario. This OptiCritical analysis produced data for each breakage scenario including the resulting pressures and velocities, demands that can no longer be supplied, and data on the customers affected. This large amount of data is processed into a criticality score for each pipe, which is combined with a probability of failure score – computed by the asset management data of pipe leakage history and ages. This combined metric provides a measure of the risk exposure of the network. Finally, a multi-objective optimisation to minimise the risk exposure, maximise the hydraulic performance and minimise the capital cost was run on the network to identify optimal capital plans for Visalia.

CJ Arms & Associates

Project: Reedbed Passive Wastewater Treatment Trial

The Reedbed Passive Wastewater Management System transforms raw sewerage into Class C water. It consists of three vegetated stages of treatment – a free draining vertical flow reedbed, a saturated vertical flow reedbed and a saturated aerated vertical flow reedbed. The first and third stages are aerobic, and the second stage is anaerobic. The system is controlled and monitored automatically, with the ability to operate the system remotely. The project minimises greenhouse gas emissions, while being the only existing wastewater treatment plant that is carbon neutral. It uses 10-15% of the energy required to fuel a mechanical treatment plant, while reducing operating and maintenance costs by 80-90%. This innovation could be transferred to numerous applications. It has the capacity to take wastewater from countless industries and be applied just as effectively. Upon completion, the system has the potential to be scaled and rolled out across sewerage plants around Australia.


Project: Sentek IRRi Link

Sentek has developed a wireless, cost-effective profiling probe measuring soil moisture, soil salinity and soil temperature at multiple 10cm soil depth levels. It is the world-first probe where data collected every 15 minutes can be downloaded via Bluetooth to a mobile phone and then uploaded to the Sentek IrriMAX Live irrigation management cloud platform. User-friendly irrigation management graphs with soil water status information and field irrigation priorities can be viewed on the same phone anywhere in the world with access to the internet.  Even if there is no internet access available in the field, the current moisture values can be displayed in the phone App for immediate decision making. Data will be automatically uploaded to the cloud if an internet connection is detected again by the phone. Sentek’s new sensor data transmission platform will allow all irrigation farmers in the world to afford a simple measurement and management tool as agricultural crop production using irrigation increasingly requires integrated sensor networks to help measure and manage crop production in a more efficient and sustainable way.

Swan Systems

Project: Swan Systems – Scheduling Water and Nutrients

Swan Systems – Scheduling Water and Nutrients – optimises application of water and nutrients to deliver productivity and optimisation of resources to irrigation industries including agricultural, horticultural, public open space, school and sports grounds, land developers and recycled water users. SWAN has been created as a cloud-based data analytics system that combines the latest technologies with a customised science-based approach to optimising water and nutrient application. SWAN’s overall architecture is designed as a management tool for water and nutrient management including planning, notification, and alerts and reporting functionality.  Its simplicity of use belies the level of sophistication behind the algorithms employed. Telemetry is used to enable the collection of data including current and forecast weather, soil moisture and actual water application from irrigation controllers. The data is processed with reference to soil characteristics, crop types, growth stages and irrigation hardware capability to deliver advice to customers’ on-line device(s). Customers benefit from increased water use efficiency, lower input costs, easier budgeting and planning, improved environmental outcomes, and efficient reporting and tracking for improved accountability and traceability.

Stantec Australia

Project: Demand Forecasting using Machine Learning

SA Water has undertaken a project to expand and enhance a set of decision support tools for its Operations Control Group. The Demand Forecast Tool (DFT) is a critical component of the tools and is used daily as part of business as usual. Stantec lead a number of improvements made to the DFT, including a new process for developing and calibrating the DFT regression model using Microsoft Azure's Machine Learning platform to forecast climate dependent water network demands. Additional improvements included a geographic expansion for the demand forecast and region specific input data to capture differences between metro and outer metro customer behaviour and climate. Work was also undertaken to validate, monitor and improve forecast accuracy of the tool. In updating the demand forecast tool calibration to use the Azure platform, SA Water has leveraged its existing system architecture to integrate into the existing DFT process and provided greater access to users to the calibration steps for further refinements, investigations and improvements.