Citation: Markiewicz, M.; Skala, A.; Grela, J.; Janusz, S.; Stasiak, T.; Lato´ n, D.; Bielecki, A.; Ba ´ nczyk, K. The Architecture for Testing Central Heating Control Algorithms with Feedback from Wireless Temperature Sensors. Energies 2023, 16, 5584. https://doi.org/10.3390/ en16145584 Academic Editor: Gerardo Maria Mauro Received: 30 May 2023 Revised: 20 July 2023 Accepted: 21 July 2023 Published: 24 July 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article The Architecture for Testing Central Heating Control Algorithms with Feedback from Wireless Temperature Sensors Michal Markiewicz 1,2, * , Aleksander Skala 3 , Jakub Grela 3 , Szymon Janusz 2 , Tadeusz Stasiak 4 , Dominik Lato ´ n 3 , Andrzej Bielecki 5, * and Katarzyna Ba ´ nczyk 3 1 Faculty of Mathematics and Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 6, 30-348 Cracow, Poland 2 Atner Sp. z o.o., ul. Podole 60, 30-394 Cracow, Poland; szymon.janusz@atner.pl 3 Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Kraków, al. Mickiewicza 30, 30-059 Cracow, Poland; skala@agh.edu.pl (A.S.); jgrela@agh.edu.pl (J.G.); laton@agh.edu.pl (D.L.) 4 Honeywell Sp. z o.o., ul. Domaniewska 39, 02-672 Warsaw, Poland; tadeusz.stasiak@honeywell.com 5 Chair of Applied Computer Science, Faculty of Electrical Engineering, Automation, Computer Science and Biomedical Engineering, AGH University of Kraków, 30-059 Cracow, Poland * Correspondence: markiewicz@ii.uj.edu.pl (M.M.); bielecki@agh.edu.pl (A.B.) Abstract: The energy consumption of buildings is a significant contributor to overall energy con- sumption in developed countries. Therefore, there is great demand for intelligent buildings in which energy consumption is optimized. Online control is a crucial aspect of such optimization. The imple- mentation of modern algorithms that take advantage of developments in information technology, artificial intelligence, machine learning, sensors, and the Internet of Things (IoT) is used in this context. In this paper, an architecture for testing central heating control algorithms as well as the control algorithms of the heating system of the building is presented. In particular, evaluation metrics, the method for seamless integration, and the mechanism for real-time performance monitoring and control are put forward. The proposed tools have been successfully tested in a residential building, and the conducted tests confirmed the efficiency of the proposed solution. Keywords: central heating; HVAC; artificial intelligence; wireless temperature sensors 1. Introduction Heating, ventilation, and air conditioning (HVAC) systems are responsible for ther- mal comfort and air quality. In the European Union, buildings consume around 40% of total energy [1,2]. The member states must ensure that new buildings, and also some existing buildings, will meet certain energy requirements [3]. This is one of the reasons for switching to renewable energy sources [4] and for the development of clean energy generation [5]. Moreover, rising energy prices and global discussions regarding the state of the environment are driving more interest in adapting central heating control systems in residential and office buildings to improve energy efficiency while maintaining the thermal comfort of their occupants. This modernization usually requires the replacement of actuators, sensors, and the local controller (the latter with one that has extended features and capabilities). Observation that every closed loop control system—including central heating systems—has a feedback mechanism led us to the conclusion that this can be ex- ploited to pass some additional information to the existing control system, with minimum modifications. Improved control algorithms can be executed on a separate computing unit, exchanging only corrections of the parameters computed by a legacy local controller. This modular approach reduces the cost of the installation and also simplifies the evaluation of the modified system performance. Comparing the updated system with the legacy one involves turning off corrections provided by optimization algorithms. New algorithms, Energies 2023, 16, 5584. https://doi.org/10.3390/en16145584 https://www.mdpi.com/journal/energies