This research paper proposes an innovative approach to urban waste management using intelligent methods of classification, clustering, and forecasting. The application of this approach allows for more efficient waste management and contributes to the sustainable development of the urban environment. The aim of this research is to develop an intelligent method for urban waste management, which includes clustering of waste sources, accurate forecasting of waste volumes, and evaluation of forecast results. To achieve this goal, a real dataset with city characteristics and waste data was used. On account of the war in Ukraine, the authors faced the problem of obtaining open data on waste in Ukraine, so it was decided to use data from another city (Singapore). The results show the high efficiency of the developed method. Comparison of the obtained results with the results of the nearest similar works shows that the main feature of this study is the high accuracy of waste-volume forecasting using the XGBoost model, which reached a level of up to 98%.

A proposed multilevel method of sensors data coding allows to increase the useful channel capacity of the data transmission protocols for Wireless Sensor Networks.

Digital twin platforms for smart cities must continuously receive different types of data from sensors, gateways, and services, but in real situations these data are heterogeneous in terms of indicator names, measurement units, time rules, and object identification, which makes integrations expensive and fragile, while second verification becomes complicated. In this paper, a minimal semantic core for “first-stage” telemetry receiving of the DTwin platform, where semantics are used as operational rules during data ingestion. The core includes a machine-readable model of entities and relationships, dictionaries of metrics and measurement units, a unified event format with separation into a stable envelope and payload, formal validation against data schemas, a mapping table for transforming raw fields into standardized measurements [name, value, unit], as well as an ingestion service with canonicalization of the event record and integrity control through the SHA-256 cryptographic hash. The implementation ensures ingestion of correct events, rejection of incorrect ones without recording, and reproducible verification through control examples, a testing protocol, and evidence snapshots. In smart city settings, such a telemetry ingestion foundation can support reliable monitoring of municipal buildings and infrastructure, including energy efficiency, indoor environmental quality, and data-driven operational decision-making. The proposed approach establishes a core for the stable integration of different sensor data into digital twins and further scaling of the platform.

Embedded computer systems with autonomous power supply is now widely used in many sectors of the economy. One of the problems that is faced by the developers of embedded systems is have to increase battery life without recharging. In this scientific work we present the creation measurement system with improved properties of average pulse energy consumers, that is based on measuring instant current values, which was proposed in the patent number 90922 issued in June 10, 2010 Ukraine.