This abstract describes how a context recognition system and a configuration planner can interact to enable personalised activity monitoring in apartments with different features. The two systems are developed to supporting independent living of senior citizens (primary users) by monitoring their daily interaction with the environment. For this purpose, networked non-intrusive sensors that senses motion, power usage, and pressure are used, in addition relevant physiological parameters such as heart rate and blood pressure are measured on demand. The system allows social interaction and timely involvement of family and caregivers, and is being developed within the European Commission FP7 project GiraffPlus [2]. The GiraffPlus system also contains a telepresence robot and an interface for caregivers and medical specialists (secondary users), to personalise and visualise data, alarms, and reminders for events of interest that have been permitted by the senior citizen. The environment is modelled as a collection of state variables that represent the layout of the apartment, position and motion of individuals and items (e.g. person1 in bedroom, book1 on table in bedroom), status of items in the apartment (e.g. light on/off, door open/closed), or physiological parameters (e.g. heart-rate of person1, weight of person1). Values of state variables are directly observable through sensors, or indirectly derivable from other state variables. There are also purely computational processes that refines sensed data to various levels of abstraction. Now, consider an apartment with networked sensors (glucose, motion), actuators (alarms) and programs, as illustrated in the right hand side of Figure 1. Different apartments may be equipped with different sensors at different positions, have different layout and furniture, and all of the former can change position or be updated over time. In this way, the set of activities that are monitored and they way in which they are inferred varies between homes and can change over time. A configuration planner is being developed in order to enable activity monitoring under such varying conditions. The purpose of the configuration planner in the GiraffPlus project is to provide the context recognition with the data it requires for recognizing the activities requested by the users. When the physical setup of the apartment is represented in a domain along with the types of data the sensors handle, the effects of actuators, and the programs available for data processing, a configuration planner can be requested to obtain information or have desirable effects into the environment, by generating information flows from