Monitoring of Bulk Water Storage and Supply System using Cloud Middleware

Kalkitech December 25, 2023

Customer: Water utility in Oceania region

Industry: Water Utility 

Business Case: 

The client is a govt owned statutory corporation responsible for supplying a state's bulk water needs, operating the state's river systems and dams, and the bulk water supply system with multiple dams across the state. Client supplies two-thirds of the water used in regional towns, irrigators, and local water utilities. The client also owns and operates one of the largest surface and groundwater monitoring networks.

As part of transforming operational business processes, the client had planned to launch an OT & IT system up-gradation. Key objectives of the upgrade included service and efficiency improvement, Centralized management of water information, Consolidation of IT systems, and Mitigation of risks. It is estimated that the project would bring benefits of two million USD per annum from 2024 by improving the business process. The client has over 5,000 monitoring stations to measure the quality and quantity of water in the rivers, streams, groundwater bores, and dams across the region of operation. Around 1200 of the remote stations continuously monitor water sources delivering real-time data through its telemetry and remote data capture devices and networks. These devices include data loggers, flow meters, weather stations, temperature sensors, RTUs/PLCs, etc. These devices measure parameters such as river heights, Streamflow, Dam and reservoir level and volumes, Groundwater bores, Meteorology, and rainfall.

The client has selected the Microsoft Azure cloud platform to deploy Centralized management of water information to improve service quality and operational efficiency. Analytics software required telemetry data from field assets on a near real-time basis. There are multiple types of devices installed in the field that are supplied by different manufacturers, communicating on different protocols. It was an enormous challenge for IT system integrators who develops the analytics applications to integrate device-specific communication adaptors in the Azure/ analytics app.

The Solution: data acquisition middleware proved to be a perfect fit to integrate different field devices into Azure IoT cloud applications. With its ready to use 100+ device protocol options to collect telemetry data from different types of field devices, data acquisition middleware is deployed as a telemetry head-end hosted on client’s Azure cloud to establish communication with field devices like data loggers, flow meters, RTUs/PLCs using DNP3.0, Modbus, and Pakbus protocols. Device data is exposed to Azure IoT Hub over a unified interface which helps analytics application collects data and manage field devices easily.

Apart from the data acquisition service, is used to perform device management functions. The device management functions include monitoring of the device connectivity health status, device communication statistics, device telemetry packet viewing/logging, device remote connect, etc. for all devices. It also involves sending, receiving, and modifying device program files for devices that support remote program management features.

In the deployed system, Azure IoT Applications can fully control all the device management, and data acquisition functions externally for all the devices communicating on different protocols. Onboarding of devices in Azure IoT Hub, triggers device twin mirror being created in Users can schedule data acquisition, or trigger on-demand data acquisition, conduct device management from Azure IoT hub using’s “Azure connector”. It enables users/applications in Azure IoT to interact with the devices using the Azure IoT device twin features and without having to deal with device-specific variations in information models and interfaces. Similarly, when data is successfully collected by, it is the “Azure connector” that pushes instantaneous data to Azure IoT Hub as twin data and historical profile data as messages.

Key Benefits: telemetry headend helped the client to provision, integrate and manage various telemetry devices efficiently from Azure IoT regardless of the type of devices, helps faster deployment of business analytics to improve service quality and improvement of operational efficiency.

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