Building a digital model of a “smart city” in the context of rapid development of technical infrastructure requires effective methods for monitoring and managing engineering systems. One of the key tasks is to optimize the placement of measuring devices in systems such as water and energy supply, including gas, electricity and heat. In conditions of limited financial resources and the need to ensure high monitoring accuracy, it is important to take into account not only the geographical distribution of consumers, but also the intensity of their load. This is especially important for managing distributed technical systems, where it is necessary to minimize equipment costs, while ensuring full network coverage and timely detection of anomalies. The purpose of this study is to develop a methodology for the optimal placement of measuring devices in engineering systems that takes into account both the spatial location of consumers and their load. The paper uses a multilevel analysis strategy using Ward’s method for hierarchical clustering and the k-means algorithm. Based on the proposed methodology, four territorial clusters were identified using the example of the Gomel water supply system, on the basis of which 20 pressure sensors were distributed proportionally to the contribution of consumption. The article shows how multiparameter clustering can be used to determine optimal centers for placing measuring devices that are focused on more powerful consumers, while taking into account the geographic distribution of objects as a whole. The developed approach allows for the efficient distribution of measuring devices taking into account the actual load of objects in the system and their geographic location, which ensures the best coverage of the territory under conditions of a limited amount of equipment. The approach presented in the article can be adapted for various technical systems, ensuring universality and flexibility of application.