## 5 Case Study: Experimental Validation in a Representative Smart Building Scenario
### Implementation of the JFML-IoT-Based Energy Management System
#### 5.4.1 Sensor and Actuator Object Instantiation
Overall, this scenario highlights the fuzzy controller's capability to

* Adjust lighting outputs in a spatially differentiated manner, reducing illumination in well-lit, occupied areas while compensating for low-light conditions in unoccupied zones to maintain a visually balanced environment;
* Manage conflicting HVAC demands by integrating humidity, temperature, and air quality indicators, leading to a moderated system response;
* Provide interpretable and adaptive control actions through the coordination of multiple overlapping rules in a heterogeneous indoor context. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Input Variable** & **Value** & **Input Variable** & **Value** \\ \hline RoomTemperature1 & 20.0 °C & RoomTemperature2 & 21.0 °C \\ RoomHumidity1 & 85.0\% & RoomHumidity2 & 80.0\% \\ Occupancy1 & 0 & Occupancy2 & 1 \\ Illuminance1 & 50.0 lx & Illuminance2 & 850.0 lx \\ CO2 Level & 400.0 ppm & – & – \\ \hline \hline \end{tabular}
\end{table} 
Table 18: Input values for Scenario S5. \begin{table}
\begin{tabular}{l l c c} \hline \hline
**Rule** & **Description** & \multicolumn{2}{c}{**Membership Degree**} \\ \hline R05 & IF RoomTemperature2 IS Medium AND Occupancy2 IS True THEN HVACControl IS Low & 0.8 \\ R10 & IF Illuminance2 IS High THEN LightingControl2 IS Off & 0.5 \\ R13 & IF Illuminance1 IS Low AND Occupancy1 IS False AND Occupancy2 IS True THEN LightingControl1 IS & 0.83 \\ Dim & R17 & CO2 Level IS Low THEN VentilationControl IS Off & 1.0 \\ R22 & IF RoomHumidity2 IS High AND Occupancy2 IS True AND RoomTemperature2 IS Medium THEN & 0.5 \\ HVACControl IS High & R24 & IF Occupancy1 IS True OR Occupancy2 IS True THEN HVACControl IS Medium, VentilationControl IS & 1.0 \\ Moderate, LightingControl1 IS Dim, LightingControl2 IS Dim & & \\ \hline \hline \end{tabular}
\end{table} 
Table 19: Inference results and active rules for Scenario S5. ### General Performance Remarks

The proposed system demonstrated adequate performance in managing the different systems available in the room based on the information provided by the sensors, enabling energy-efficient operation while maintaining a comfortable environment for the occupants and preventing hazardous gas concentrations. The system's behavior across all tested scenarios supports its suitability for intelligent building control, while also offering a high degree of interpretability. This transparency allows domain experts to understand, validate, and refine the system's decisions--particularly in cases where behaviors may be suboptimal--thus facilitating adaptation to user-specific needs and preventing undesired actions in similar future situations. For instance, rule R24 is designed to initiate system activation at a baseline comfort level when occupancy is detected. Other rules then modulate system behavior in response to the room's specific environmental conditions. If a stronger emphasis on energy savings is desired, rule R24 can be removed to reduce baseline energy usage. However, such a change would require careful redesign of the rule base, potentially involving the addition of new rules to preserve comfort while minimizing consumption. The use of FRBSs to manage IoT infrastructures aligns with established guidelines and supports compliance with the European Union's AI Act ([[https://artificialintelligenceact.eu/](https://artificialintelligenceact.eu/)]([https://artificialintelligenceact.eu/](https://artificialintelligenceact.eu/)), accessed on 16 July 2025), which promotes the development of trustworthy artificial intelligence systems. By ensuring interpretability and transparency, these systems can build user trust and confidence in AI-driven automation. Additionally, the low cost of the proposed solution makes it a promising candidate for implementing efficient energy management strategies in low-performing buildings across the European space, contributing to cost reductions for both citizens and small enterprises.