Construct a commonsense knowledge model of activities in urban leisure space with the Spreading Activation Theory With the coming of ubiquitous computing era, academic researches and industries put more efforts in the development of the sensor structure, to create a digital environment which can sense, adapt, and react to the activities of human beings with the sensor being put into the ambient intelligence. But in most of the research results, the ability of sensors is emphasized and less attention is paid to the construction of logical structure regarding people’s everyday life experiences. The main purpose of sensor technology is to sense and detect the activities and behaviors of human beings. People have similar or the same habits in their behaviors, such a habit will naturally be accumulated in the space and become the patterns of activities. Consequently, urban leisure activity is set to be the theme in this research. By collecting various activities and events of human beings in urban plazas, dependencies are further analyzed. The interactive data based on users’ cumulative usage are explored. For the establishment of the rule of activities in future smart urban space, main contribution made by this research is to develop a set of simple and formalized approach, to construct the commonsense knowledge model of activities in urban leisure space by recording the behavior patterns of human beings, and to provide a reference for digitized support and service in the future. The commonsense knowledge model of activities in urban leisure space is called “SmartCypin”, the algorithm of the spreading activation model is adopted. Each behavior node is inferred based on the possibility of what behavior may happen next and on their mutual relationships. In the spreading activation model, various weights are put into certain nodes and checked to see if some behavior nodes are enabled under such a circumstance. In the future development of smart urban space, smart can be woven into the activity patterns of the nature, allowing mutual relationships to form an information network.
