## 1 Introduction  
Energy efficiency in buildings represents a critical component of modern infrastructure, driven by the need to reduce operating costs, minimize environmental impact, and adhere to increasingly stringent energy regulations. Since buildings account for a substantial portion of global energy consumption, optimizing their energy use is essential for achieving sustainability goals [1, 2]. For instance, approximately 85% of buildings in the European Union (EU) were constructed before 2000, and among these, 75% exhibit low energy performance, so enhancing the energy efficiency of these buildings is essential for conserving energy, reducing costs for both citizens and small businesses, and advancing toward a zero-emission and fully decarbonized building stock by 2050. In response, on 28 May 2024, the EU revised the Energy Performance of Buildings Directive (EU/2024/1275) entered into force in all EU countries to foster an accelerated rate of renovation, particularly among the worst-performing buildings ([[https://energy.ec.europa.eu/topics/energy-efficiency/energy-efficient-buildings/energy-performance-buildings-directive_en](https://energy.ec.europa.eu/topics/energy-efficiency/energy-efficient-buildings/energy-performance-buildings-directive_en)]([https://energy.ec.europa.eu/topics/energy-efficiency/energy-efficient-buildings/energy-performance-buildings-directive_en](https://energy.ec.europa.eu/topics/energy-efficiency/energy-efficient-buildings/energy-performance-buildings-directive_en)), accessed on 16 July 2025). Traditional techniques for energy efficiency in buildings include advanced lighting control systems that use dimmable LED lighting combined with daylight harvesting strategies to minimize electricity consumption [3]. Ventilation systems employ demand-controlled ventilation (DCV) using CO\({}_{2}\) sensors to adjust airflow based on occupancy [4], while noise reduction techniques incorporate sound-absorbing materials and active noise cancellation strategies to enhance indoor comfort [5]. Occupancy detection technologies, such as passive infrared (PIR) sensors, ultrasonic sensors, and computer vision-based systems, help dynamically adjust heating, ventilation, and air conditioning (HVAC) settings to optimize energy usage [6]. These approaches, while effective, often rely on rigid rule-based automation that lacks adaptability to real-time environmental fluctuations and varying occupancy patterns. The Internet of Things (IoT) has emerged as a transformative paradigm for real-time data acquisition, processing, and automation in smart environments, including building energy management [7; 8; 9]. IoT enables interconnected sensors, actuators, and controllers to collect and analyze environmental and operational data, allowing for more efficient and adaptive energy usage strategies. In the context of energy-efficient buildings, IoT applications include smart thermostats that optimize HVAC performance based on occupancy patterns [10], intelligent lighting systems that adjust brightness levels according to daylight availability [11], and energy monitoring systems that provide real-time feedback on consumption trends [12]. Furthermore, IoT facilitates predictive maintenance by continuously monitoring equipment performance, reducing energy waste caused by faulty systems [13]. Despite these advancements, many IoT-based solutions for energy management lack standardization, security, interoperability, and the ability to process uncertain or incomplete or missing data, limiting their effectiveness in complex and dynamic building environments [14; 15; 16]. Addressing these limitations requires a more intelligent decision-making framework capable of handling uncertainty and optimizing energy consumption dynamically. Artificial intelligence (AI) and fuzzy logic-based systems provide an effective approach for dealing with the inherent uncertainty in complex environments such as smart buildings [17; 18].