The present thesis describes the results of a study to capture patterns of user control actions in an office building in Vienna, Austria with regard to buildings' technical systems for heating, cooling and lighting based on a long-term study. It describes an effort to observe control-oriented occupant behavior in 29 offices of a large high-rise office complex over a period of one year. Specifically, states and events pertaining to occupancy, building systems, indoor environment, and external environment were monitored. A weather station, a number of indoor data loggers, and two digital cameras were used to continuously monitor - and record every five minutes - such events and states: occupancy, indoor and outdoor temperature and relative humidity, internal illuminance, external air velocity and horizontal global irradiance, status of electrical light fixtures, position of shades. The main task of the project is to monitor and analyze the behavior of the monitored occupants for providing a better understanding of occupants' interactions with building energy systems.
Upon the analysis of the collected data, this work explores a number of hypothesized relationships between the nature and frequency of the control actions on one side and the magnitude and dynamism of indoor and outdoor environmental changes on the other side. The results reveal distinct patterns in the collected data. Specifically, control behavior tendencies show dependencies both on indoor environmental conditions and outdoor environmental parameters. A summary of these tendencies is presented. These kinds of relationships have the potential to provide the basis of behavioral models for control-oriented user actions in buildings. Such models can subsequently be integrated in comprehensive building information models to support facility management and indoor environmental control operations in buildings. Moreover, the modeling of occupants' behavior would make possible to predict the influence of the human factor on the building environment and increase the accuracy of the energy performance predictions and improving occupants' comfort.