This study presents the design and simulation of a server room feasibility evaluation system using the Mamdani Fuzzy Logic approach. The system evaluates three environmental parameters: temperature, relative humidity, and airborne particle concentration. A total of 27 IF–THEN rules were developed based on operational considerations and international environmental recommendations. Triangular membership functions were applied to represent normal operating conditions to enhance sensitivity, while trapezoidal functions were used for extreme conditions to ensure response stability under sensor uncertainty. The inference process employed the minimum operator for rule activation, maximum aggregation, and centroid defuzzification to produce a quantitative feasibility score within a 0–100 scale. Simulation results demonstrate that the fuzzy approach provides smoother and more adaptive decision boundaries compared to crisp logic, enabling gradual evaluation of transitional environmental conditions. A case study simulation confirmed that variations in humidity and particulate levels significantly influence the final feasibility score, even when temperature remains within the recommended range. Furthermore, rescaling the particle concentration domain (0–200 µg/m³) improved system sensitivity for indoor pollutant monitoring. The proposed system proves effective as a decision-support tool for intelligent server room environmental monitoring.
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