<![CDATA[This study analyzes passenger elevator operation patterns and their contribution to building electricity consumption in a university lecture building. Previous research has mainly focused on system simulations or control optimization, resulting in limited empirical studies that integrate large-scale directional passenger movement data with aggregated building-level electricity consumption, especially in academic settings. To address this gap, the study examines elevator usage patterns based on 31,265 observed trips and links directional travel with building-level electricity consumption. Data were collected over a two-week period (13–24 October 2025) through direct observation and MDP-based energy measurements, then analyzed using Pearson correlation and linear regression. Results show that 44.6% of total traffic occurred in the morning, with 83.0% concentrated during peak periods. Upward trips accounted for 52.7% of movements, indicating directional asymmetry associated with increased traction motor load during peak hours. Pearson correlation analysis revealed a significant positive relationship between elevator usage intensity and daily electricity consumption (r = 0.813, p = 0.004, 95% CI [0.35–0.96]). Linear regression showed that 66.1% of variation in daily energy consumption could be explained by elevator usage intensity. This study provides a context-specific empirical analysis by integrating directional elevator travel data with aggregated building-level electricity consumption in a university lecture building, based on real-world observations. These findings demonstrate that dominant upward travel during academic transition periods is measurably associated with overall building energy consumption dynamics.]]>
