Efficient Heating System Management Through IoT Smart Devices

  1. Álvaro de la Puente Gil 1
  2. Alberto González Martínez 1
  3. Enrique Rosales-Asensio 2
  4. Ana María Diez Suárez 1
  5. Jorge Juan Blanes Peiró 1
  1. 1 ERESMA Research Group, Escuela Superior y Técnica de Ingenieros de Minas, Department of Electrical Engineering, Systems and Automation, Universidad de León, Campus de Vegazana s/n, 24071 León, Spain
  2. 2 Department of Electrical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Spain
Journal:
Machines

ISSN: 2075-1702

Year of publication: 2025

Volume: 13

Issue: 8

Pages: 643

Type: Article

DOI: 10.3390/MACHINES13080643 GOOGLE SCHOLAR lock_openOpen access editor HANDLE: https://hdl.handle.net/10612/26569

More publications in: Machines

BULERIA. Repositorio Institucional de la Universidad de León: lock_openOpen access Handle

Abstract

A novel approach to managing domestic heating systems through IoT technologies is introduced in this paper. The system optimizes energy consumption by dynamically adapting to electricity and fuel price fluctuations while maintaining user comfort. Integrating smart devices significantly reduce energy costs and offer a favorable payback period, positioning the solution as both sustainable and economically viable. Efficient heating management is increasingly critical amid growing energy and environmental concerns. This strategy uses IoT devices to collect real-time data on prices, consumption, and user preferences. Based on this data, the system adjusts heating settings intelligently to balance comfort and cost savings. IoT connectivity manages continuous monitoring and dynamic optimization in response to changing conditions. This study includes a real-case comparison between a conventional central heating system and an IoT-managed electric radiator setup. By applying automation rules linked to energy pricing and user habits, the system enhances energy efficiency, especially in cold climates. The economic evaluation shows that using low-cost IoT devices yields meaningful savings and achieves equipment payback within approximately three years. The results demonstrate the system’s effectiveness, demonstrating that smart, adaptive heating solutions can cut energy expenses without sacrificing comfort, while offering environmental and financial benefits.

Bibliographic References

  • Kraus, (2019), Rev. Manag. Sci., 13, pp. 519, 10.1007/s11846-019-00333-8
  • Sivaraman, (2018), IEEE Technol. Soc. Mag., 37, pp. 71, 10.1109/MTS.2018.2826079
  • European Commission (2015). Directorate General for Communication. Energía: Energía Sostenible, Segura y Asequible para los Europeos, Publications Office.
  • (2023, October 23). IPCC—Intergovernmental Panel on Climate Change. Available online: https://archive.ipcc.ch/home_languages_main_spanish.shtml.
  • (2021, June 07). Climate Change Physical Basis. Available online: https://www.miteco.gob.es/ca/ceneam/recursos/materiales/cambio-climatico-bases-fisicas.aspx.
  • The Intergovernmental Panel on Climate Change (2018). Global Warming of 1.5 °C, Publications Office.
  • International Energy Agency (IEA) (2021). Energy Efficiency 2021, Publications Office.
  • (2022, October 26). IEA—International Energy Agency. Available online: https://www.iea.org.
  • (2024, September 16). Residential Buildings: Energy Efficiency & Consumption Evolution in Europe. Available online: https://www.enerdata.net/publications/executive-briefing/households-energy-efficiency.html.
  • INE (2023, May 26). National Institute of Statistics INE. Instituto Nacional de Estadística. Available online: https://www.ine.es/.
  • (2022, December 31). Ministry for Ecological Transition and the Demographic Challenge. Available online: https://www.miteco.gob.es/es/.
  • European Environment Agency’s (2020). European Environment Agency’s, Publications Office.
  • Rogelj, (2018), Nat. Clim. Chang., 8, pp. 325, 10.1038/s41558-018-0091-3
  • Mansouri, A., Wei, W., Alessandrini, J.-M., Mandin, C., and Blondeau, P. (2022). Impact of Climate Change on Indoor Air Quality: A Review. Int. J. Environ. Res. Public Health, 19.
  • Pavlatos, C., Makris, E., Fotis, G., Vita, V., and Mladenov, V. (2023). Utilization of Artificial Neural Networks for Precise Electrical Load Prediction. Technologies, 11.
  • Hettiarachchi, D.G., Jaward, G.M.A., Tharaka, V.P.V., Jeewandara, J.M.D.S., and Hemapala, K.T.M.U. (2021, January 24). IoT Based Building Energy Management System. Proceedings of the 2021 3rd International Conference on Electrical Engineering (EECon), Colombo, Sri Lanka.
  • Zhang, (2022), Renew. Sustain. Energy Rev., 165, pp. 112560, 10.1016/j.rser.2022.112560
  • Raval, (2021), Internet Things, 13, pp. 100354, 10.1016/j.iot.2020.100354
  • (2023, November 11). Meteorologisk Institutt. Available online: https://www.met.no/.
  • Pantelic, (2023), Energy Build., 286, pp. 112932, 10.1016/j.enbuild.2023.112932
  • Płaczek, B. (2023). A Multi-Agent Prediction Method for Data Sampling and Transmission Reduction in Internet of Things Sensor Networks. Sensors, 23.
  • de la Puente-Gil, Á., de Simón-Martín, M., González-Martínez, A., Diez-Suárez, A.-M., and Blanes-Peiró, J.-J. (2023). The Internet of Things for the Intelligent Management of the Heating of a Swimming Pool by Means of Smart Sensors. Sensors, 23.
  • Rind, Y.M., Raza, M.H., Zubair, M., Mehmood, M.Q., and Massoud, Y. (2023). Smart Energy Meters for Smart Grids, an Internet of Things Perspective. Energies, 16.
  • Zalba, (2023), Energy Build., 285, pp. 112882, 10.1016/j.enbuild.2023.112882
  • Orumwense, (2023), AIMS Electron. Electr. Eng., 7, pp. 50, 10.3934/electreng.2023004
  • Masroor, (2023), Adv. Build. Energy Res., 17, pp. 345, 10.1080/17512549.2023.2208117
  • Zualkernan, (2017), IEEE Trans. Consum. Electron., 63, pp. 426, 10.1109/TCE.2017.015014
  • Heidari, (2023), Sustain. Comput. Inform. Syst., 39, pp. 100899
  • Li, (2020), Nat. Commun., 11, pp. 6101, 10.1038/s41467-020-19790-x
  • Gholamzadehmir, (2020), Sustain. Cities Soc., 63, pp. 102480, 10.1016/j.scs.2020.102480
  • Nilsson, (2018), Energy Build., 179, pp. 15, 10.1016/j.enbuild.2018.08.026
  • Sarbu, I., Mirza, M., and Muntean, D. (2022). Integration of Renewable Energy Sources into Low-Temperature District Heating Systems: A Review. Energies, 15.
  • Malkawi, (2023), Energy Build., 295, pp. 113291, 10.1016/j.enbuild.2023.113291
  • Krarti, (2020), Energy Build., 220, pp. 110047, 10.1016/j.enbuild.2020.110047
  • Persson, (2009), Appl. Energy, 86, pp. 645, 10.1016/j.apenergy.2008.07.004
  • Sepasgozar, S., Karimi, R., Farahzadi, L., Moezzi, F., Shirowzhan, S., Ebrahimzadeh, S.M., Hui, F., and Aye, L. (2020). A Systematic Content Review of Artificial Intelligence and the Internet of Things Applications in Smart Home. Appl. Sci., 10.
  • IEA (International Energy Agency) (2014). Energy Efficiency Indicators: Fundamentals on Statistics, International Energy Agency.
  • (2024, November 26). PD: Psychrometric Chart. Available online: https://drajmarsh.bitbucket.io/psychro-chart2d.html.
  • Assistant, H. (2025, July 04). Home Assistant. Available online: https://www.home-assistant.io/.
  • Abdelouhahid, R.A., Debauche, O., Mahmoudi, S., Marzak, A., Manneback, P., and Lebeau, F. (2020, January 24–26). Open Phytotron: A New IoT Device for Home Gardening. Proceedings of the 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech), Marrakesh, Morocco.
  • Hossein Motlagh, N., Khatibi, A., and Aslani, A. (2020). Toward Sustainable Energy-Independent Buildings Using Internet of Things. Energies, 13.
  • Ang, (2023), Nat. Commun., 14, pp. 1689, 10.1038/s41467-023-37131-6
  • Saeed, M.A., Eladl, A.A., Alhasnawi, B.N., Motahhir, S., Nayyar, A., Shah, M.A., and Sedhom, B.E. (2023). Energy Management System in Smart Buildings Based Coalition Game Theory with Fog Platform and Smart Meter Infrastructure. Sci. Rep., 13.
  • Government of Spain (2025, July 04). Real Decreto 897/2017, de 6 de Octubre, por el que se Regula la Figura del Consumidor Vulnerable, el Bono Social y Otras Medidas de Protección para los Consumidores Domésticos de Energía Eléctrica, Available online: https://www.boe.es/eli/es/rd/2017/10/06/897.
  • (2007). Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics. Standard No. EN 15251.
  • Abilkhassenova, (2023), Energy Build., 297, pp. 113479, 10.1016/j.enbuild.2023.113479
  • Hou, (2023), Energy Build., 301, pp. 113581, 10.1016/j.enbuild.2023.113581
  • Annebicque, (2016), IFAC-Pap., 49, pp. 313
  • Krishnan, P., Prabu, A.V., Loganathan, S., Routray, S., Ghosh, U., and AL-Numay, M. (2023). Analyzing and Managing Various Energy-Related Environmental Factors for Providing Personalized IoT Services for Smart Buildings in Smart Environment. Sustainability, 15.
  • Tzeiranaki, (2021), Energy Strategy Rev., 36, pp. 100680, 10.1016/j.esr.2021.100680
  • Lin, (2023), ACM Trans. Internet Technol., 22, pp. 105:1