RESEARCH OF METHODS FOR OPTIMIZATION OF SMART HOME CONTROL SYSTEM PARAMETERS USING IOT

DOI 10.31673/2412-4338.2025.013027

Authors

  • Дмитро Олександрович Ніщеменко, (Nishchemenko Dmytro) State university of information and communication technologies, Kyiv Central Ukrainian State University, Kropyvnytskyi https://orcid.org/0009-0006-1781-4109
  • Андрій Олексійович Аронов, (Aronov Andrii) State University of Information and Communication Technologies, Kyiv https://orcid.org/0009-0000-7868-8341

Abstract

The development of the Internet of Things (IoT) significantly transforms approaches to managing living conditions, enabling the integration of devices for monitoring energy consumption, climate parameters, and security. However, the increasing complexity of IoT systems poses new challenges, including the need for adaptive management, device compatibility, and efficient resource optimization. This study characterizes the concept of a smart home as an integrated system based on a combination of sensors, actuators, centralized management systems, and communication protocols (MQTT, Zigbee, ZWave). Methods for energy consumption forecasting, including machine learning, neural networks, and statistical models, are examined. Optimization algorithms, such as genetic algorithms and fuzzy logic methods, are analyzed for their potential to reduce energy consumption and enhance comfort. Special attention is given to embedded operating systems (FreeRTOS, RIOT OS, Zephyr OS), highlighting their advantages and disadvantages in terms of energy efficiency, security, and support for network protocols. The study explores issues related to IoT platform integration, such as the diversity of protocols and the lack of unified standards, which complicate interoperability between devices from different manufacturers. Zephyr OS is identified as the most promising platform for further research due to its flexibility, energy efficiency, and support for key IoT protocols. The conclusions outline proposals for future research, including improving energy consumption forecasting methods, developing optimization algorithms for smart home management, and creating unified information technologies for integrating IoT devices into a cohesive system. The findings emphasize the importance of advancing existing technologies to ensure the energy efficiency, adaptability, and security of smart homes.

Keywords: Internet of Things, smart home, forecasting algorithms, genetic algorithm, embedded operating systems, IoT protocols

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Published

2025-04-07

Issue

No. 1 (2025)

Section

Articles