Utility management demands two basic functions for an optimal automation scenario, which are monitoring and control. Here, we report a novel approach utilizing free spectrum communication technology and the Internet of Things (IoT) framework for Water Distribution Network (WDN) management. We make use of an architecture combining the free spectrum protocols included in the ISM (Industrial, Scientific, and Medical) radio band, along with cloud-based data management. The main aspects of the developed system are user-friendly operation and control, along with reliable and fault-free operation. In this paper, we discuss, in detail, the architecture, hardware design, and software applications associated with the IoT-based wireless monitoring and control of WDNs.

The Internet of Things (IoT) has become an integral part of today’s smart and digitally connected world. IoT devices and technologies now connect almost every aspect of daily life, generating, storing, and analysing vast amounts of data. One important use of IoT is in utility management, where essential services such as water are supplied through IoT-enabled infrastructure to ensure fair, efficient, and sustainable delivery. The large volumes of data produced by water distribution networks must be safeguarded against manipulation, theft, and other malicious activities. Incidents such as the Queensland user data breach (2020–21), the Oldsmar water treatment plant attack (2021), and the Texas water system overflow (2024) show that attacks on water treatment plants, distribution networks, and supply infrastructure are common in Australia and worldwide, often due to inadequate security measures and limited technical resources. Lightweight cryptographic algorithms are particularly valuable in this context, as they are well-suited for resource-constrained hardware commonly used in IoT systems. This study focuses on the in-house developed ChaosFortress lightweight cryptographic algorithm, comparing its performance with other widely used lightweight cryptographic algorithms. The evaluation and comparative testing used an Arduino and a LoRa-based transmitter/receiver pair, along with the NIST Statistical Test Suite (STS). These tests assessed the performance of ChaosFortress against popular lightweight cryptographic algorithms, including ACORN, Ascon, ChaChaPoly, Speck, tinyAES, and tinyECC. ChaosFortress was equal in performance to the other algorithms in overall memory management but outperformed five of the six in execution speed. ChaosFortress achieved the quickest transmission time and topped the NIST STS results, highlighting its strong suitability for IoT applications.

Data Driven Monitoring of IOT enabled Water Distribution Networks

In this paper, we present results from a study on leak detection based on graph partitioning. Leaks are isolated using graph partitioning and performing mass balances over the partitions. The algorithms are tested and validated using a scaled-down test facility such as the Reconfigurable Testbed for Control and Operation of WDN (RTCOP-WDN). The benefits and limitations of the presented techniques along with the required hardware to test these leak detection methods are discussed.