Towards Commonsense Reasoning in AAL Environments

Ambient Assisted Living (AAL) is an application of Smart Environments, dealing with elderlies and their caregivers’ assistance in their daily life within their enhanced apartments. An AAL environment needs constant observation of the inhabitant’s activities to inform caregivers of critical situations respectively to react to them, such as the patient leaving the flat with the stove still on. Setting up an AAL environment is costly and complicated, as all sensors are tailored to the specific situation. Various industrial systems or research activities exist to monitor the environment and apply a rule-based inference to detect the multiple conditions as far as possible. There are, however, a range of standard day-to-day sensors, such as light switches, window sensors etc., which do not directly monitor patient conditions but allow for inference about a situation, e.g. whether a person has left the flat. We call this “lifted” contextual information. Also, there is much uncertainty in such environments, such as sensor malfunctions, power loss, or connectivity issues. Hence, a situation awareness system should freely combine and switch between combinations of sensors for identifying and verifying the current situation, respectively, inferences drawn from it. For example, confirm that the person has left the flat by checking for a webcam movement. This resembles our ability to use commonsense when we look at possible sensor readings on a dashboard. We make plain inferences based on a hypothesis on the given evidence. Such a system needs to make logical connections between different data and contribute to a derived information. We propose developing a logic-based system using the sensor events as evidence for a commonsense reasoning task.