Interpretable Fuzzy Control for Energy Management in Smart Buildings Using JFML-IoT and IEEE Std 1855-2016 Martínez Rojas, María Cano Gutiérrez, Carlos Alcalá Fernández, Jesús Soto Hidalgo, José Manuel smart buildings energy management fuzzy rule-based systems IEEE Std 1855-2016 fuzzy markup language internet of things This paper presents an interpretable and modular framework for energy management in smart buildings based on fuzzy logic and the IEEE Std 1855-2016. The proposed system builds upon the JFML-IoT library, enabling the integration and execution of fuzzy rule-based systems on resource-constrained IoT devices using a lightweight and extensible architecture. Unlike conventional data-driven controllers, this approach emphasizes semantic transparency, expert-driven control logic, and compliance with fuzzy markup standards. The system is designed to enhance both operational efficiency and user comfort through transparent and explainable decision-making. A four-layer architecture structures the system into Perception, Communication, Processing, and Application layers, supporting real-time decisions based on environmental data. The fuzzy logic rules are defined collaboratively with domain experts and encoded in Fuzzy Markup Language to ensure interoperability and formalization of expert knowledge. While adherence to IEEE Std 1855-2016 facilitates system integration and standardization, the scientific contribution lies in the deployment of an interpretable, IoT-based control system validated in real conditions. A case study is conducted in a realistic indoor environment, using temperature, humidity, illuminance, occupancy, and CO2 sensors, along with HVAC and lighting actuators. The results demonstrate that the fuzzy inference engine generates context-aware control actions aligned with expert expectations. The proposed framework also opens possibilities for incorporating user-specific preferences and adaptive comfort strategies in future developments. 2025-09-01T09:11:31Z 2025-09-01T09:11:31Z 2025-07-23 journal article Martínez-Rojas, M., Cano, C., Alcalá-Fdez, J., & Soto-Hidalgo, J. M. (2025). Interpretable Fuzzy Control for Energy Management in Smart Buildings Using JFML-IoT and IEEE Std 1855-2016. Applied Sciences, 15 (15), 8208. https://doi.org/10.3390/app15158208 https://hdl.handle.net/10481/105906 10.3390/app15158208 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional