ABSTRACT Leakages in water supply networks can be minimized through pressure reduction or by repairing the resulting damage. The effective implementation of the latter approach necessitates the localization of leaks, for which various methods exist. This paper presents a specific software and hardware configuration for constructing a digital twin of pressurized piping systems that can be utilized for this purpose. The proposed method can identify both the flow and position of leaks and is based on solving an equivalent optimization problem, where the objective function depends on the difference between the measured pressure values at specific points and those predicted at the same points under the same boundary conditions by a computational model. Given the multimodality of the formulated problem, particle swarm optimization is implemented for this task. To enable real-time localization, the measured pressure values are transmitted to a microcontroller, which processes the data and sends it to a Python script. This script employs a while loop to continuously monitor the criteria for leak detection, and when these criteria are met, it initiates a procedure for leak localization. The theoretical aspect of the procedure, as well as its practical implementation, is presented below as an example.