Towards Continuous Activity Monitoring with Temporal Constraints
Jonas Ullberg, Amy Loutfi, Federico Pecora · 2009
Public demand for intelligent services in their home environments can be ex-pected to grow in the near future once the required technology becomes more widely available and mature. Many intelligent home services cannot be pro-vided in a purely reactive fashion though since they require contextual knowl-edge about the environment and most importantly the activities the residents are engaged in at any given time. This poses a problem since information about a human’s behavior is not easily accessible and has to be recognized from ag-gregated sensor data in most cases. Numerous activity recognition techniques have been studied in the literature. In this thesis we focus on one such technique which takes a temporal reasoning approach to activity recognition, namely rec-ognizing activities by planning for them with a temporal planner. OMPS is an example of such a planner that has been used in previous work to recognize activities of humans in domestic environments. An important requirement for monitoring activities in a real world application is the ability to do so con-tinuously and reliably. Two shortcomings in the previous approach hindered OMPS’s capability to meet this requirement, namely maintaining the perfor-mance of the activity recognition over long monitoring horizons, and ensuring future temporal consistency of recognized activities. This thesis will define the two problems, detail their solutions, and finally evaluate the modified system with the corresponding changes implemented. 7