Abstract

A low-cost IoT-based monitoring system has been developed to collect and analyze energy data from the main electrical distribution panel of the College of Engineering and Natural Sciences (CENS) building at Malatya Turgut Özal University. Within the scope of the study, energy consumption profiles of the college building have been analyzed based on the collected data. Using the developed energy monitoring device, three-phase voltage, current, active power, reactive power, and energy consumption data have been read from the energy analyzer device at one-minute resolution, transferred via the RS485 communication protocol and stored on a server. In this paper, daily consumption profiles have been created with hourly resolution based on the data collected between February 3 and April 20, 2025, corresponding to the Spring semester of the 2024–2025 academic year. Using k-means clustering algorithm, daily consumption profiles have been segmented, and three different consumption patterns have been identified. Upon examining these consumption patterns, usage intensity-related consumption patterns of the building have been revealed and interpreted. As the result, the findings demonstrate that implementing IoT-based energy monitoring systems in higher education buildings significantly contributes to revealing detailed energy consumption characteristics and, consequently, to the development of effective energy efficiency strategies.

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