Sciact
  • EN
  • RU

Human-Centered Energy Consumption Advising System of Smart Home Full article

Journal Applied Sciences
, E-ISSN: 2076-3417
Output data Year: 2026, Volume: 16, Number: 20, Article number : 10287, Pages count : DOI: 10.3390/app162010287
Tags smart home; symbiotic system; electricity consumption; energy forecasting; flexible tariffs
Authors Kalimoldayev M. 1 , Barakhnin V. 1,2 , Berikov V. 1,3 , Alekankin K. 4 , Kladov D. 3
Affiliations
1 Institute of Information and Computational Technologies, Almaty, 050010, Kazakhstan
2 Federal Research Center for Information and Computational Technologies, Novosibirsk 630090, Russia
3 Sobolev Institute of Mathematics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk 630090, Russia
4 HSE Tikhonov Moscow Institute of Electronics and Mathematics, National Research University “Higher School of Economics”, Moscow 101000, Russia

Abstract: This article examines concepts of human–machine interaction that support a human-centered approach: cybersocial systems of Industry 5.0 and symbiotic systems. It analyzes the potential for creating symbiotic smart home systems. It also looks into the most common tasks solved by smart homes in the area of electricity consumption, such as analyzing and forecasting energy consumption within the system and developing recommendations for smart home ecosystem participants based on this analysis and forecast. The mutual influence of these tasks in a symbiotic smart home system is demonstrated. It proposes an approach to identifying typical energy consumption scenarios and interpreting consumer behavior. It develops an ensemble learning algorithm for time series forecasting based on clustering. The article also explores the feasibility of implementing the concept of rational consumption and generating recommendations for shifting consumption to periods with lower tariffs based on household electricity consumption forecasting.
Cite: Kalimoldayev M. , Barakhnin V. , Berikov V. , Alekankin K. , Kladov D.
Human-Centered Energy Consumption Advising System of Smart Home
Applied Sciences. 2026. V.16. N20. 10287 . DOI: 10.3390/app162010287 WOS Scopus OpenAlex
Dates:
Submitted: Sep 11, 2026
Accepted: Oct 9, 2026
Published online: Oct 17, 2026
Identifiers:
≡ Web of science: WOS:001912577200001
≡ Scopus: 2-s2.0-105055011552
≡ OpenAlex: W7222974923
Altmetrics: